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null | nemo | hf_model_name = f'{username}/{MODEL_NAME}'
TEMPLATE = f"""
## Model Overview
<DESCRIBE IN ONE LINE THE MODEL AND ITS USE>
## NVIDIA NeMo: Training
To train, fine-tune or play with the model you will need to install [NVIDIA NeMo](https://github.com/NVIDIA/NeMo). We recommend you install it after you've installed lat... | {} | dastmard/stt_en_conformer_ctc_small | null | [
"nemo",
"region:us"
] | null | 2022-07-09T13:25:05+00:00 | [] | [] | TAGS
#nemo #region-us
| hf_model_name = f'{username}/{MODEL_NAME}'
TEMPLATE = f"""
## Model Overview
<DESCRIBE IN ONE LINE THE MODEL AND ITS USE>
## NVIDIA NeMo: Training
To train, fine-tune or play with the model you will need to install NVIDIA NeMo. We recommend you install it after you've installed latest Pytorch version.
## How to ... | [
"## Model Overview\n\n<DESCRIBE IN ONE LINE THE MODEL AND ITS USE>",
"## NVIDIA NeMo: Training\n\nTo train, fine-tune or play with the model you will need to install NVIDIA NeMo. We recommend you install it after you've installed latest Pytorch version.",
"## How to Use this Model\n\nThe model is available for ... | [
"TAGS\n#nemo #region-us \n",
"## Model Overview\n\n<DESCRIBE IN ONE LINE THE MODEL AND ITS USE>",
"## NVIDIA NeMo: Training\n\nTo train, fine-tune or play with the model you will need to install NVIDIA NeMo. We recommend you install it after you've installed latest Pytorch version.",
"## How to Use this Model... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_wav2vec2_s732
Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your spee... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_wav2vec2_s732 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T13:33:03+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_wav2vec2_s732
Fine-tuned facebook/wav2vec2-large-lv60 for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_wav2vec2_s732\n\nFine-tuned facebook/wav2vec2-large-lv60 for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_wav2vec2_s732\n\nFine-tuned facebook/wav2vec2-large-lv60 for speech recognition using the train split of Common Voi... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_vp-100k_s108
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make ... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_vp-100k_s108 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T14:01:02+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_vp-100k_s108
Fine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_vp-100k_s108\n\nFine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_vp-100k_s108\n\nFine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition using the train split of C... |
image-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# vit-base-avengers-v1
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "model-index": [{"name": "vit-base-avengers-v1", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "args": "a... | dingusagar/vit-base-avengers-v1 | null | [
"transformers",
"pytorch",
"tensorboard",
"vit",
"image-classification",
"generated_from_trainer",
"dataset:imagefolder",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T14:05:01+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #vit #image-classification #generated_from_trainer #dataset-imagefolder #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| vit-base-avengers-v1
====================
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5324
* Accuracy: 0.8683
Refer to this medium article for more info on how it was trained.
Limitations
-... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0002\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 4\n* mixed\\_prec... | [
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"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learnin... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_vp-100k_s904
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make ... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_vp-100k_s904 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T14:16:17+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_vp-100k_s904
Fine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_vp-100k_s904\n\nFine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_vp-100k_s904\n\nFine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition using the train split of C... |
token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlm-roberta-base-finetuned-panx-de
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-b... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["xtreme"], "metrics": ["f1"], "model-index": [{"name": "xlm-roberta-base-finetuned-panx-de", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "xtreme", "type": "xtreme", "args": "PAN-X.de"}, "me... | huangjia/xlm-roberta-base-finetuned-panx-de | null | [
"transformers",
"pytorch",
"tensorboard",
"xlm-roberta",
"token-classification",
"generated_from_trainer",
"dataset:xtreme",
"license:mit",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T14:23:57+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #xlm-roberta #token-classification #generated_from_trainer #dataset-xtreme #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us
| xlm-roberta-base-finetuned-panx-de
==================================
This model is a fine-tuned version of xlm-roberta-base on the xtreme dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1333
* F1: 0.8551
Model description
-----------------
More information needed
Intended uses & l... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 48\n* eval\\_batch\\_size: 48\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
"### Traini... | [
"TAGS\n#transformers #pytorch #tensorboard #xlm-roberta #token-classification #generated_from_trainer #dataset-xtreme #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 ... | {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | pligor/TEST1-PPO-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-07-09T14:29:50+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
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] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
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"## Usage (with Stable-baselines3)\nTODO: Add you... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-turkish-colab
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["common_voice"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-turkish-colab", "results": []}]} | marifulhaque/wav2vec2-large-xls-r-300m-turkish-colab | null | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"dataset:common_voice",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T14:31:57+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-turkish-colab
=======================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common\_voice dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4411
* Wer: 0.3271
Model description
-----------------
More informat... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 32\n* optimizer: Adam with betas=(0.9,0.999) and epsilon... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* t... |
text-generation | transformers |
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1475310547805425664/2vnS... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "http://www.huggingtweets.com/bro_b619/1657381637888/predictions.png", "widget": [{"text": "My dream is"}]} | huggingtweets/bro_b619 | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-07-09T14:37:02+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
AI BOT
Brutha B
@bro\_b619
I was made with huggingtweets.
Create your own bot based on your favorite user with the demo!
How does it work?
-----------------
The model uses the following pipeline.
!pipeline
To understand how the model was developed, check the W&B report.
Training data
------------... | [] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlm-roberta-base-finetuned-panx-de-fr
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-robert... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["f1"], "model-index": [{"name": "xlm-roberta-base-finetuned-panx-de-fr", "results": []}]} | huangjia/xlm-roberta-base-finetuned-panx-de-fr | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"generated_from_trainer",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T14:47:40+00:00 | [] | [] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us
| xlm-roberta-base-finetuned-panx-de-fr
=====================================
This model is a fine-tuned version of xlm-roberta-base on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1584
* F1: 0.8537
Model description
-----------------
More information needed
Intended uses... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 48\n* eval\\_batch\\_size: 48\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
"### Traini... | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 48\n*... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_vp-100k_s847
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make ... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_vp-100k_s847 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T14:48:01+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_vp-100k_s847
Fine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_vp-100k_s847\n\nFine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_vp-100k_s847\n\nFine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition using the train split of C... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_xlsr-53_s328
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_xlsr-53_s328 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T14:51:39+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_xlsr-53_s328
Fine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_xlsr-53_s328\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_xlsr-53_s328\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition using the train split of Common V... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_xlsr-53_s131
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_xlsr-53_s131 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T14:55:50+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_xlsr-53_s131
Fine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_xlsr-53_s131\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_xlsr-53_s131\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition using the train split of Common V... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_xlsr-53_s624
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_xlsr-53_s624 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T14:59:44+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_xlsr-53_s624
Fine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_xlsr-53_s624\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_xlsr-53_s624\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition using the train split of Common V... |
token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlm-roberta-base-finetuned-panx-fr
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-b... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["xtreme"], "metrics": ["f1"], "model-index": [{"name": "xlm-roberta-base-finetuned-panx-fr", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "xtreme", "type": "xtreme", "args": "PAN-X.fr"}, "me... | huangjia/xlm-roberta-base-finetuned-panx-fr | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"generated_from_trainer",
"dataset:xtreme",
"license:mit",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T15:00:27+00:00 | [] | [] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #generated_from_trainer #dataset-xtreme #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us
| xlm-roberta-base-finetuned-panx-fr
==================================
This model is a fine-tuned version of xlm-roberta-base on the xtreme dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2739
* F1: 0.8204
Model description
-----------------
More information needed
Intended uses & l... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 48\n* eval\\_batch\\_size: 48\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
"### Traini... | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #generated_from_trainer #dataset-xtreme #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n... |
reinforcement-learning | ml-agents |
# **ppo** Agent playing **Pyramids**
This is a trained model of a **ppo** agent playing **Pyramids** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://github.com/huggingface/ml-agents#get-started
We wrote a comple... | {"library_name": "ml-agents", "tags": ["unity-ml-agents", "ml-agents", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-Pyramids"]} | ryanblak/testpyramidsrnd | null | [
"ml-agents",
"tensorboard",
"onnx",
"unity-ml-agents",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-Pyramids",
"region:us"
] | null | 2022-07-09T15:01:20+00:00 | [] | [] | TAGS
#ml-agents #tensorboard #onnx #unity-ml-agents #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Pyramids #region-us
|
# ppo Agent playing Pyramids
This is a trained model of a ppo agent playing Pyramids using the Unity ML-Agents Library.
## Usage (with ML-Agents)
The Documentation: URL
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
### Resume the trainin... | [
"# ppo Agent playing Pyramids\n This is a trained model of a ppo agent playing Pyramids using the Unity ML-Agents Library.\n \n ## Usage (with ML-Agents)\n The Documentation: URL\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n\n\n ### Resume the t... | [
"TAGS\n#ml-agents #tensorboard #onnx #unity-ml-agents #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Pyramids #region-us \n",
"# ppo Agent playing Pyramids\n This is a trained model of a ppo agent playing Pyramids using the Unity ML-Agents Library.\n \n ## Usage (with ML-Agents)\n The Documen... |
token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlm-roberta-base-finetuned-panx-it
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-b... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["xtreme"], "metrics": ["f1"], "model-index": [{"name": "xlm-roberta-base-finetuned-panx-it", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "xtreme", "type": "xtreme", "args": "PAN-X.it"}, "me... | huangjia/xlm-roberta-base-finetuned-panx-it | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"generated_from_trainer",
"dataset:xtreme",
"license:mit",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T15:05:43+00:00 | [] | [] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #generated_from_trainer #dataset-xtreme #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us
| xlm-roberta-base-finetuned-panx-it
==================================
This model is a fine-tuned version of xlm-roberta-base on the xtreme dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2687
* F1: 0.7938
Model description
-----------------
More information needed
Intended uses & l... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 48\n* eval\\_batch\\_size: 48\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
"### Traini... | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #generated_from_trainer #dataset-xtreme #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n... |
token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlm-roberta-base-finetuned-panx-en
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-b... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["xtreme"], "metrics": ["f1"], "model-index": [{"name": "xlm-roberta-base-finetuned-panx-en", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "xtreme", "type": "xtreme", "args": "PAN-X.en"}, "me... | huangjia/xlm-roberta-base-finetuned-panx-en | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"generated_from_trainer",
"dataset:xtreme",
"license:mit",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T15:09:31+00:00 | [] | [] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #generated_from_trainer #dataset-xtreme #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us
| xlm-roberta-base-finetuned-panx-en
==================================
This model is a fine-tuned version of xlm-roberta-base on the xtreme dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4603
* F1: 0.6181
Model description
-----------------
More information needed
Intended uses & l... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 48\n* eval\\_batch\\_size: 48\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
"### Traini... | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #generated_from_trainer #dataset-xtreme #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n... |
token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlm-roberta-base-finetuned-panx-all
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["f1"], "model-index": [{"name": "xlm-roberta-base-finetuned-panx-all", "results": []}]} | huangjia/xlm-roberta-base-finetuned-panx-all | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"generated_from_trainer",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T15:13:01+00:00 | [] | [] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us
| xlm-roberta-base-finetuned-panx-all
===================================
This model is a fine-tuned version of xlm-roberta-base on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1709
* F1: 0.8561
Model description
-----------------
More information needed
Intended uses & l... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 48\n* eval\\_batch\\_size: 48\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
"### Traini... | [
"TAGS\n#transformers #pytorch #xlm-roberta #token-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 48\n*... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_unispeech_s149
Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_unispeech_s149 | null | [
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T15:18:30+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_unispeech_s149
Fine-tuned microsoft/unispeech-large-1500h-cv for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_unispeech_s149\n\nFine-tuned microsoft/unispeech-large-1500h-cv for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #unispeech #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_unispeech_s149\n\nFine-tuned microsoft/unispeech-large-1500h-cv for speech recognition using the train split of Co... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_unispeech_s449
Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_unispeech_s449 | null | [
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T15:29:45+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_unispeech_s449
Fine-tuned microsoft/unispeech-large-1500h-cv for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_unispeech_s449\n\nFine-tuned microsoft/unispeech-large-1500h-cv for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #unispeech #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_unispeech_s449\n\nFine-tuned microsoft/unispeech-large-1500h-cv for speech recognition using the train split of Co... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_unispeech_s358
Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_unispeech_s358 | null | [
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T15:37:04+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_unispeech_s358
Fine-tuned microsoft/unispeech-large-1500h-cv for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_unispeech_s358\n\nFine-tuned microsoft/unispeech-large-1500h-cv for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #unispeech #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_unispeech_s358\n\nFine-tuned microsoft/unispeech-large-1500h-cv for speech recognition using the train split of Co... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_hubert_s805
Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech i... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_hubert_s805 | null | [
"transformers",
"pytorch",
"hubert",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T15:45:18+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #hubert #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_hubert_s805
Fine-tuned facebook/hubert-large-ll60k for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_hubert_s805\n\nFine-tuned facebook/hubert-large-ll60k for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #hubert #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_hubert_s805\n\nFine-tuned facebook/hubert-large-ll60k for speech recognition using the train split of Common Voice 7.... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_hubert_s730
Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech i... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_hubert_s730 | null | [
"transformers",
"pytorch",
"hubert",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T15:53:11+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #hubert #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_hubert_s730
Fine-tuned facebook/hubert-large-ll60k for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_hubert_s730\n\nFine-tuned facebook/hubert-large-ll60k for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #hubert #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_hubert_s730\n\nFine-tuned facebook/hubert-large-ll60k for speech recognition using the train split of Common Voice 7.... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_hubert_s930
Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech i... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_hubert_s930 | null | [
"transformers",
"pytorch",
"hubert",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T15:57:59+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #hubert #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_hubert_s930
Fine-tuned facebook/hubert-large-ll60k for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_hubert_s930\n\nFine-tuned facebook/hubert-large-ll60k for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #hubert #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_hubert_s930\n\nFine-tuned facebook/hubert-large-ll60k for speech recognition using the train split of Common Voice 7.... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_vp-sv_s363
Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_vp-sv_s363 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T16:05:06+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_vp-sv_s363
Fine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_vp-sv_s363\n\nFine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_vp-sv_s363\n\nFine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition using the train split of Commo... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_vp-sv_s331
Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_vp-sv_s331 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T16:19:40+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_vp-sv_s331
Fine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_vp-sv_s331\n\nFine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_vp-sv_s331\n\nFine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition using the train split of Commo... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_vp-sv_s116
Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_vp-sv_s116 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T16:27:07+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_vp-sv_s116
Fine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_vp-sv_s116\n\nFine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_vp-sv_s116\n\nFine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition using the train split of Commo... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_no-pretraining_s910
Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model ... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_no-pretraining_s910 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T16:30:18+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_no-pretraining_s910
Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_no-pretraining_s910\n\nFine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_no-pretraining_s910\n\nFine-tuned randomly initialized wav2vec2 model for speech recognition using the train split ... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_no-pretraining_s705
Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model ... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_no-pretraining_s705 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T16:33:28+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_no-pretraining_s705
Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_no-pretraining_s705\n\nFine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_no-pretraining_s705\n\nFine-tuned randomly initialized wav2vec2 model for speech recognition using the train split ... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 ... | {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | croumegous/ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-07-09T16:34:50+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add you... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_no-pretraining_s630
Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model ... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_no-pretraining_s630 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T16:36:47+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_no-pretraining_s630
Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_no-pretraining_s630\n\nFine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_no-pretraining_s630\n\nFine-tuned randomly initialized wav2vec2 model for speech recognition using the train split ... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_wavlm_s132
Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampl... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_wavlm_s132 | null | [
"transformers",
"pytorch",
"wavlm",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T16:40:12+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wavlm #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_wavlm_s132
Fine-tuned microsoft/wavlm-large for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_wavlm_s132\n\nFine-tuned microsoft/wavlm-large for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wavlm #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_wavlm_s132\n\nFine-tuned microsoft/wavlm-large for speech recognition using the train split of Common Voice 7.0 (sv-SE... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_wavlm_s42
Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sample... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_wavlm_s42 | null | [
"transformers",
"pytorch",
"wavlm",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T16:43:30+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wavlm #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_wavlm_s42
Fine-tuned microsoft/wavlm-large for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_wavlm_s42\n\nFine-tuned microsoft/wavlm-large for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wavlm #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_wavlm_s42\n\nFine-tuned microsoft/wavlm-large for speech recognition using the train split of Common Voice 7.0 (sv-SE)... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_wavlm_s607
Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampl... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_wavlm_s607 | null | [
"transformers",
"pytorch",
"wavlm",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T16:46:54+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wavlm #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_wavlm_s607
Fine-tuned microsoft/wavlm-large for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_wavlm_s607\n\nFine-tuned microsoft/wavlm-large for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wavlm #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_wavlm_s607\n\nFine-tuned microsoft/wavlm-large for speech recognition using the train split of Common Voice 7.0 (sv-SE... |
null | null | ---
tags:
- conversational--- | {} | roborisq/FetEWapBot | null | [
"region:us"
] | null | 2022-07-09T16:47:08+00:00 | [] | [] | TAGS
#region-us
| ---
tags:
- conversational--- | [] | [
"TAGS\n#region-us \n"
] |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_unispeech-ml_s35
Fine-tuned [microsoft/unispeech-large-multi-lingual-1500h-cv](https://huggingface.co/microsoft/unispeech-large-multi-lingual-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_unispeech-ml_s35 | null | [
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T16:50:09+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_unispeech-ml_s35
Fine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_unispeech-ml_s35\n\nFine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #unispeech #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_unispeech-ml_s35\n\nFine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the t... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_unispeech-ml_s729
Fine-tuned [microsoft/unispeech-large-multi-lingual-1500h-cv](https://huggingface.co/microsoft/unispeech-large-multi-lingual-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
Whe... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_unispeech-ml_s729 | null | [
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T16:53:33+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_unispeech-ml_s729
Fine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_unispeech-ml_s729\n\nFine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #unispeech #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_unispeech-ml_s729\n\nFine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the ... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_unispeech-ml_s664
Fine-tuned [microsoft/unispeech-large-multi-lingual-1500h-cv](https://huggingface.co/microsoft/unispeech-large-multi-lingual-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
Whe... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_unispeech-ml_s664 | null | [
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T16:56:58+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_unispeech-ml_s664
Fine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_unispeech-ml_s664\n\nFine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #unispeech #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_unispeech-ml_s664\n\nFine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the ... |
reinforcement-learning | ml-agents |
# **ppo** Agent playing **Pyramids**
This is a trained model of a **ppo** agent playing **Pyramids** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://github.com/huggingface/ml-agents#get-started
We wrote a comple... | {"library_name": "ml-agents", "tags": ["unity-ml-agents", "ml-agents", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-Pyramids"]} | meln1k/MLAgents-Pyramids | null | [
"ml-agents",
"tensorboard",
"onnx",
"unity-ml-agents",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-Pyramids",
"region:us"
] | null | 2022-07-09T16:58:19+00:00 | [] | [] | TAGS
#ml-agents #tensorboard #onnx #unity-ml-agents #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Pyramids #region-us
|
# ppo Agent playing Pyramids
This is a trained model of a ppo agent playing Pyramids using the Unity ML-Agents Library.
## Usage (with ML-Agents)
The Documentation: URL
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
### Resume the trainin... | [
"# ppo Agent playing Pyramids\n This is a trained model of a ppo agent playing Pyramids using the Unity ML-Agents Library.\n \n ## Usage (with ML-Agents)\n The Documentation: URL\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n\n\n ### Resume the t... | [
"TAGS\n#ml-agents #tensorboard #onnx #unity-ml-agents #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Pyramids #region-us \n",
"# ppo Agent playing Pyramids\n This is a trained model of a ppo agent playing Pyramids using the Unity ML-Agents Library.\n \n ## Usage (with ML-Agents)\n The Documen... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_vp-fr_s79
Fine-tuned [facebook/wav2vec2-large-fr-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-fr-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure th... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_vp-fr_s79 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T17:00:36+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_vp-fr_s79
Fine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_vp-fr_s79\n\nFine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_vp-fr_s79\n\nFine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition using the train split of Common... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_vp-fr_s387
Fine-tuned [facebook/wav2vec2-large-fr-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-fr-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_vp-fr_s387 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T17:04:34+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_vp-fr_s387
Fine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_vp-fr_s387\n\nFine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_vp-fr_s387\n\nFine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition using the train split of Commo... |
token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# lmv2-g-w9-293-doc-07-09
This model is a fine-tuned version of [microsoft/layoutlmv2-base-uncased](https://huggingface.co/microso... | {"license": "cc-by-nc-sa-4.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "lmv2-g-w9-293-doc-07-09", "results": []}]} | Sebabrata/lmv2-g-w9-293-doc-07-09 | null | [
"transformers",
"pytorch",
"tensorboard",
"layoutlmv2",
"token-classification",
"generated_from_trainer",
"license:cc-by-nc-sa-4.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T17:05:35+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #layoutlmv2 #token-classification #generated_from_trainer #license-cc-by-nc-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us
| lmv2-g-w9-293-doc-07-09
=======================
This model is a fine-tuned version of microsoft/layoutlmv2-base-uncased on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0031
* Address Precision: 1.0
* Address Recall: 1.0
* Address F1: 1.0
* Address Number: 59
* Business Name P... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 4e-05\n* train\\_batch\\_size: 1\n* eval\\_batch\\_size: 1\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* num\\_epochs: 30",
"### Train... | [
"TAGS\n#transformers #pytorch #tensorboard #layoutlmv2 #token-classification #generated_from_trainer #license-cc-by-nc-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 4e-05\n* tra... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_vp-fr_s237
Fine-tuned [facebook/wav2vec2-large-fr-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-fr-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_vp-fr_s237 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T17:08:01+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_vp-fr_s237
Fine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_vp-fr_s237\n\nFine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_vp-fr_s237\n\nFine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition using the train split of Commo... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 ... | {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | richx86/ppoLunarLanderv2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-07-09T17:08:01+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add you... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_vp-es_s399
Fine-tuned [facebook/wav2vec2-large-es-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-es-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_vp-es_s399 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T17:11:03+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_vp-es_s399
Fine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_vp-es_s399\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_vp-es_s399\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Commo... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_vp-es_s869
Fine-tuned [facebook/wav2vec2-large-es-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-es-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_vp-es_s869 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T17:15:12+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_vp-es_s869
Fine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_vp-es_s869\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_vp-es_s869\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Commo... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_vp-es_s408
Fine-tuned [facebook/wav2vec2-large-es-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-es-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_vp-es_s408 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T17:20:50+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_vp-es_s408
Fine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_vp-es_s408\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_vp-es_s408\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Commo... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_vp-nl_s764
Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_vp-nl_s764 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T17:24:42+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_vp-nl_s764
Fine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_vp-nl_s764\n\nFine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_vp-nl_s764\n\nFine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Commo... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_vp-nl_s842
Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_vp-nl_s842 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T17:28:21+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_vp-nl_s842
Fine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_vp-nl_s842\n\nFine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_vp-nl_s842\n\nFine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Commo... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_vp-nl_s615
Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_vp-nl_s615 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T17:32:19+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_vp-nl_s615
Fine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_vp-nl_s615\n\nFine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_vp-nl_s615\n\nFine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Commo... |
text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# gpt2-small-spanish-historias-conflicto-col
This model is a fine-tuned version of [datificate/gpt2-small-spanish](https://hugging... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "gpt2-small-spanish-historias-conflicto-col", "results": []}]} | jorge-henao/gpt2-small-spanish-historias-conflicto-col | null | [
"transformers",
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | null | 2022-07-09T17:38:01+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us
| gpt2-small-spanish-historias-conflicto-col
==========================================
This model is a fine-tuned version of datificate/gpt2-small-spanish on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.2388
Model description
-----------------
More information needed
I... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 6\n* eval\\_batch\\_size: 6\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
"### Training... | [
"TAGS\n#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learnin... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_unispeech-sat_s515
Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_unispeech-sat_s515 | null | [
"transformers",
"pytorch",
"unispeech-sat",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T17:45:05+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #unispeech-sat #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_unispeech-sat_s515
Fine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_unispeech-sat_s515\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #unispeech-sat #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_unispeech-sat_s515\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_unispeech-sat_s772
Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_unispeech-sat_s772 | null | [
"transformers",
"pytorch",
"unispeech-sat",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T17:49:21+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #unispeech-sat #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_unispeech-sat_s772
Fine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_unispeech-sat_s772\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #unispeech-sat #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_unispeech-sat_s772\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_unispeech-sat_s658
Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_unispeech-sat_s658 | null | [
"transformers",
"pytorch",
"unispeech-sat",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T17:53:13+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #unispeech-sat #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_unispeech-sat_s658
Fine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_unispeech-sat_s658\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #unispeech-sat #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_unispeech-sat_s658\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of... |
feature-extraction | transformers | # Spider-NQ: Question Encoder
This is the question encoder of the model fine-tuned on Natural Questions (and initialized from Spider) discussed in our paper [Learning to Retrieve Passages without Supervision](https://arxiv.org/abs/2112.07708).
## Usage
We used weight sharing for the query encoder and passage encoder... | {} | NAACL2022/spider-nq-question-encoder | null | [
"transformers",
"pytorch",
"dpr",
"feature-extraction",
"arxiv:2112.07708",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T17:54:41+00:00 | [
"2112.07708"
] | [] | TAGS
#transformers #pytorch #dpr #feature-extraction #arxiv-2112.07708 #endpoints_compatible #region-us
| # Spider-NQ: Question Encoder
This is the question encoder of the model fine-tuned on Natural Questions (and initialized from Spider) discussed in our paper Learning to Retrieve Passages without Supervision.
## Usage
We used weight sharing for the query encoder and passage encoder, so the same model should be applie... | [
"# Spider-NQ: Question Encoder\n\nThis is the question encoder of the model fine-tuned on Natural Questions (and initialized from Spider) discussed in our paper Learning to Retrieve Passages without Supervision.",
"## Usage\n\nWe used weight sharing for the query encoder and passage encoder, so the same model sho... | [
"TAGS\n#transformers #pytorch #dpr #feature-extraction #arxiv-2112.07708 #endpoints_compatible #region-us \n",
"# Spider-NQ: Question Encoder\n\nThis is the question encoder of the model fine-tuned on Natural Questions (and initialized from Spider) discussed in our paper Learning to Retrieve Passages without Supe... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_xls-r_s610
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech ... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_xls-r_s610 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T17:57:14+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_xls-r_s610
Fine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_xls-r_s610\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_xls-r_s610\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice ... |
null | transformers | # Spider-NQ: Context Encoder
This is the context encoder of the model fine-tuned on Natural Questions (and initialized from Spider) discussed in our paper [Learning to Retrieve Passages without Supervision](https://arxiv.org/abs/2112.07708).
## Usage
We used weight sharing for the query encoder and passage encoder, ... | {} | NAACL2022/spider-nq-ctx-encoder | null | [
"transformers",
"pytorch",
"dpr",
"arxiv:2112.07708",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T17:59:17+00:00 | [
"2112.07708"
] | [] | TAGS
#transformers #pytorch #dpr #arxiv-2112.07708 #endpoints_compatible #region-us
| # Spider-NQ: Context Encoder
This is the context encoder of the model fine-tuned on Natural Questions (and initialized from Spider) discussed in our paper Learning to Retrieve Passages without Supervision.
## Usage
We used weight sharing for the query encoder and passage encoder, so the same model should be applied ... | [
"# Spider-NQ: Context Encoder\n\nThis is the context encoder of the model fine-tuned on Natural Questions (and initialized from Spider) discussed in our paper Learning to Retrieve Passages without Supervision.",
"## Usage\n\nWe used weight sharing for the query encoder and passage encoder, so the same model shoul... | [
"TAGS\n#transformers #pytorch #dpr #arxiv-2112.07708 #endpoints_compatible #region-us \n",
"# Spider-NQ: Context Encoder\n\nThis is the context encoder of the model fine-tuned on Natural Questions (and initialized from Spider) discussed in our paper Learning to Retrieve Passages without Supervision.",
"## Usage... |
null | transformers | # Spider-TriviaQA: Context Encoder
This is the context encoder of the model fine-tuned on TriviaQA (and initialized from Spider) discussed in our paper [Learning to Retrieve Passages without Supervision](https://arxiv.org/abs/2112.07708).
## Usage
We used weight sharing for the query encoder and passage encoder, so ... | {} | NAACL2022/spider-trivia-ctx-encoder | null | [
"transformers",
"pytorch",
"dpr",
"arxiv:2112.07708",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T18:04:51+00:00 | [
"2112.07708"
] | [] | TAGS
#transformers #pytorch #dpr #arxiv-2112.07708 #endpoints_compatible #region-us
| # Spider-TriviaQA: Context Encoder
This is the context encoder of the model fine-tuned on TriviaQA (and initialized from Spider) discussed in our paper Learning to Retrieve Passages without Supervision.
## Usage
We used weight sharing for the query encoder and passage encoder, so the same model should be applied for... | [
"# Spider-TriviaQA: Context Encoder\n\nThis is the context encoder of the model fine-tuned on TriviaQA (and initialized from Spider) discussed in our paper Learning to Retrieve Passages without Supervision.",
"## Usage\n\nWe used weight sharing for the query encoder and passage encoder, so the same model should b... | [
"TAGS\n#transformers #pytorch #dpr #arxiv-2112.07708 #endpoints_compatible #region-us \n",
"# Spider-TriviaQA: Context Encoder\n\nThis is the context encoder of the model fine-tuned on TriviaQA (and initialized from Spider) discussed in our paper Learning to Retrieve Passages without Supervision.",
"## Usage\n\... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_xls-r_s926
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech ... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_xls-r_s926 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T18:05:33+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_xls-r_s926
Fine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_xls-r_s926\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_xls-r_s926\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice ... |
feature-extraction | transformers | # Spider-TriviaQA: Question Encoder
This is the question encoder of the model fine-tuned on TriviaQA (and initialized from Spider) discussed in our paper [Learning to Retrieve Passages without Supervision](https://arxiv.org/abs/2112.07708).
## Usage
We used weight sharing for the query encoder and passage encoder, s... | {} | NAACL2022/spider-trivia-question-encoder | null | [
"transformers",
"pytorch",
"dpr",
"feature-extraction",
"arxiv:2112.07708",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T18:06:50+00:00 | [
"2112.07708"
] | [] | TAGS
#transformers #pytorch #dpr #feature-extraction #arxiv-2112.07708 #endpoints_compatible #region-us
| # Spider-TriviaQA: Question Encoder
This is the question encoder of the model fine-tuned on TriviaQA (and initialized from Spider) discussed in our paper Learning to Retrieve Passages without Supervision.
## Usage
We used weight sharing for the query encoder and passage encoder, so the same model should be applied f... | [
"# Spider-TriviaQA: Question Encoder\n\nThis is the question encoder of the model fine-tuned on TriviaQA (and initialized from Spider) discussed in our paper Learning to Retrieve Passages without Supervision.",
"## Usage\n\nWe used weight sharing for the query encoder and passage encoder, so the same model should... | [
"TAGS\n#transformers #pytorch #dpr #feature-extraction #arxiv-2112.07708 #endpoints_compatible #region-us \n",
"# Spider-TriviaQA: Question Encoder\n\nThis is the question encoder of the model fine-tuned on TriviaQA (and initialized from Spider) discussed in our paper Learning to Retrieve Passages without Supervi... |
null | null | Gender Classifier
This is a model that classifies genders with 91% accuracy. Data is taken from "https://huggingface.co/datasets/myvision/gender-classification", that is a labeled pictures dataset which consist of 5000 balanced training examples, 1000 balanced validation examples, and 1000 balanced test examples.
Con... | {} | gorkemcanozkan/gender-classifier | null | [
"region:us"
] | null | 2022-07-09T18:07:09+00:00 | [] | [] | TAGS
#region-us
| Gender Classifier
This is a model that classifies genders with 91% accuracy. Data is taken from "URL that is a labeled pictures dataset which consist of 5000 balanced training examples, 1000 balanced validation examples, and 1000 balanced test examples.
Convolutional Neural Networks are used for training the model.
... | [] | [
"TAGS\n#region-us \n"
] |
null | transformers | # Spider
This is the unsupervised pretrained model discussed in our paper [Learning to Retrieve Passages without Supervision](https://arxiv.org/abs/2112.07708).
## Usage
We used weight sharing for the query encoder and passage encoder, so the same model should be applied for both.
**Note**! We format the passages s... | {} | NAACL2022/spider | null | [
"transformers",
"pytorch",
"dpr",
"arxiv:2112.07708",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T18:09:18+00:00 | [
"2112.07708"
] | [] | TAGS
#transformers #pytorch #dpr #arxiv-2112.07708 #endpoints_compatible #region-us
| # Spider
This is the unsupervised pretrained model discussed in our paper Learning to Retrieve Passages without Supervision.
## Usage
We used weight sharing for the query encoder and passage encoder, so the same model should be applied for both.
Note! We format the passages similar to DPR, i.e. the title and the te... | [
"# Spider\n\nThis is the unsupervised pretrained model discussed in our paper Learning to Retrieve Passages without Supervision.",
"## Usage\n\nWe used weight sharing for the query encoder and passage encoder, so the same model should be applied for both.\n\nNote! We format the passages similar to DPR, i.e. the t... | [
"TAGS\n#transformers #pytorch #dpr #arxiv-2112.07708 #endpoints_compatible #region-us \n",
"# Spider\n\nThis is the unsupervised pretrained model discussed in our paper Learning to Retrieve Passages without Supervision.",
"## Usage\n\nWe used weight sharing for the query encoder and passage encoder, so the same... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_xls-r_s946
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech ... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_xls-r_s946 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T18:12:36+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_xls-r_s946
Fine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_xls-r_s946\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_xls-r_s946\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice ... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_r-wav2vec2_s160
Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that you... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_r-wav2vec2_s160 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T18:17:07+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_r-wav2vec2_s160
Fine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_r-wav2vec2_s160\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_r-wav2vec2_s160\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_r-wav2vec2_s423
Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that you... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_r-wav2vec2_s423 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T18:20:54+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_r-wav2vec2_s423
Fine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_r-wav2vec2_s423\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_r-wav2vec2_s423\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_r-wav2vec2_s418
Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that you... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_r-wav2vec2_s418 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T18:24:19+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_r-wav2vec2_s418
Fine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_r-wav2vec2_s418\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_r-wav2vec2_s418\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_vp-it_s975
Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_vp-it_s975 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T18:28:43+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_vp-it_s975
Fine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_vp-it_s975\n\nFine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_vp-it_s975\n\nFine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Commo... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 ... | {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | Varnez/username-model_architecture-end_id | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-07-09T18:29:36+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add you... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_vp-it_s533
Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_vp-it_s533 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T18:32:51+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_vp-it_s533
Fine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_vp-it_s533\n\nFine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_vp-it_s533\n\nFine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Commo... |
automatic-speech-recognition | transformers | # exp_w2v2t_sv-se_vp-it_s817
Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["sv-SE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "sv-SE"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_sv-se_vp-it_s817 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T18:36:42+00:00 | [] | [
"sv-SE"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_sv-se_vp-it_s817
Fine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_sv-se_vp-it_s817\n\nFine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Common Voice 7.0 (sv-SE).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #sv-SE #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_sv-se_vp-it_s817\n\nFine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Commo... |
automatic-speech-recognition | transformers | # exp_w2v2t_fa_wav2vec2_s321
Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition using the train split of [Common Voice 7.0 (fa)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech inp... | {"language": ["fa"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "fa"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_fa_wav2vec2_s321 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fa",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T18:40:51+00:00 | [] | [
"fa"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_fa_wav2vec2_s321
Fine-tuned facebook/wav2vec2-large-lv60 for speech recognition using the train split of Common Voice 7.0 (fa).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_fa_wav2vec2_s321\n\nFine-tuned facebook/wav2vec2-large-lv60 for speech recognition using the train split of Common Voice 7.0 (fa).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_fa_wav2vec2_s321\n\nFine-tuned facebook/wav2vec2-large-lv60 for speech recognition using the train split of Common Voice 7.0... |
automatic-speech-recognition | transformers | # exp_w2v2t_fa_wav2vec2_s168
Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition using the train split of [Common Voice 7.0 (fa)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech inp... | {"language": ["fa"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "fa"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_fa_wav2vec2_s168 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fa",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T18:45:17+00:00 | [] | [
"fa"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_fa_wav2vec2_s168
Fine-tuned facebook/wav2vec2-large-lv60 for speech recognition using the train split of Common Voice 7.0 (fa).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_fa_wav2vec2_s168\n\nFine-tuned facebook/wav2vec2-large-lv60 for speech recognition using the train split of Common Voice 7.0 (fa).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_fa_wav2vec2_s168\n\nFine-tuned facebook/wav2vec2-large-lv60 for speech recognition using the train split of Common Voice 7.0... |
automatic-speech-recognition | transformers | # exp_w2v2t_fa_wav2vec2_s873
Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition using the train split of [Common Voice 7.0 (fa)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech inp... | {"language": ["fa"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "fa"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_fa_wav2vec2_s873 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fa",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T18:49:26+00:00 | [] | [
"fa"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_fa_wav2vec2_s873
Fine-tuned facebook/wav2vec2-large-lv60 for speech recognition using the train split of Common Voice 7.0 (fa).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_fa_wav2vec2_s873\n\nFine-tuned facebook/wav2vec2-large-lv60 for speech recognition using the train split of Common Voice 7.0 (fa).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_fa_wav2vec2_s873\n\nFine-tuned facebook/wav2vec2-large-lv60 for speech recognition using the train split of Common Voice 7.0... |
automatic-speech-recognition | transformers | # exp_w2v2t_fa_vp-100k_s88
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fa)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure th... | {"language": ["fa"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "fa"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_fa_vp-100k_s88 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fa",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T18:53:13+00:00 | [] | [
"fa"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_fa_vp-100k_s88
Fine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition using the train split of Common Voice 7.0 (fa).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_fa_vp-100k_s88\n\nFine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition using the train split of Common Voice 7.0 (fa).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_fa_vp-100k_s88\n\nFine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition using the train split of Common V... |
automatic-speech-recognition | transformers | # exp_w2v2t_fa_vp-100k_s407
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fa)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["fa"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "fa"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_fa_vp-100k_s407 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fa",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T18:56:44+00:00 | [] | [
"fa"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_fa_vp-100k_s407
Fine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition using the train split of Common Voice 7.0 (fa).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_fa_vp-100k_s407\n\nFine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition using the train split of Common Voice 7.0 (fa).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_fa_vp-100k_s407\n\nFine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition using the train split of Common ... |
automatic-speech-recognition | transformers | # exp_w2v2t_fa_vp-100k_s881
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fa)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["fa"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "fa"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_fa_vp-100k_s881 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fa",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T19:00:21+00:00 | [] | [
"fa"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_fa_vp-100k_s881
Fine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition using the train split of Common Voice 7.0 (fa).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_fa_vp-100k_s881\n\nFine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition using the train split of Common Voice 7.0 (fa).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_fa_vp-100k_s881\n\nFine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition using the train split of Common ... |
automatic-speech-recognition | transformers | # exp_w2v2t_fa_xlsr-53_s116
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (fa)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speec... | {"language": ["fa"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "fa"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_fa_xlsr-53_s116 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fa",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T19:04:46+00:00 | [] | [
"fa"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_fa_xlsr-53_s116
Fine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition using the train split of Common Voice 7.0 (fa).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_fa_xlsr-53_s116\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition using the train split of Common Voice 7.0 (fa).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_fa_xlsr-53_s116\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition using the train split of Common Voice 7... |
automatic-speech-recognition | transformers | # exp_w2v2t_fa_xlsr-53_s356
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (fa)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speec... | {"language": ["fa"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "fa"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_fa_xlsr-53_s356 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fa",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T19:10:09+00:00 | [] | [
"fa"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_fa_xlsr-53_s356
Fine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition using the train split of Common Voice 7.0 (fa).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_fa_xlsr-53_s356\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition using the train split of Common Voice 7.0 (fa).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_fa_xlsr-53_s356\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition using the train split of Common Voice 7... |
automatic-speech-recognition | transformers | # exp_w2v2t_fa_xlsr-53_s204
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (fa)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speec... | {"language": ["fa"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "fa"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_fa_xlsr-53_s204 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fa",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T19:14:39+00:00 | [] | [
"fa"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_fa_xlsr-53_s204
Fine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition using the train split of Common Voice 7.0 (fa).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_fa_xlsr-53_s204\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition using the train split of Common Voice 7.0 (fa).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_fa_xlsr-53_s204\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition using the train split of Common Voice 7... |
text-classification | transformers |
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# jonaskoenig/xtremedistil-l6-h256-uncased-future-time-references
This model is a fine-tuned version of [microsoft/xtremedistil-l6-h256-... | {"license": "mit", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "jonaskoenig/xtremedistil-l6-h256-uncased-future-time-references", "results": []}]} | jonaskoenig/xtremedistil-l6-h256-uncased-future-time-references | null | [
"transformers",
"tf",
"bert",
"text-classification",
"generated_from_keras_callback",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T19:17:23+00:00 | [] | [] | TAGS
#transformers #tf #bert #text-classification #generated_from_keras_callback #license-mit #autotrain_compatible #endpoints_compatible #region-us
| jonaskoenig/xtremedistil-l6-h256-uncased-future-time-references
===============================================================
This model is a fine-tuned version of microsoft/xtremedistil-l6-h256-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 0.0126
* Train Sp... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'name': 'Adam', 'learning\\_rate': 5e-05, 'decay': 0.0, 'beta\\_1': 0.9, 'beta\\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}\n* training\\_precision: float32",
"### Training results",
"### Framework... | [
"TAGS\n#transformers #tf #bert #text-classification #generated_from_keras_callback #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'name': 'Adam', 'learning\\_rate': 5e-05, 'deca... |
automatic-speech-recognition | transformers | # exp_w2v2t_fa_unispeech_s211
Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (fa)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["fa"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "fa"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_fa_unispeech_s211 | null | [
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"fa",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T19:18:16+00:00 | [] | [
"fa"
] | TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_fa_unispeech_s211
Fine-tuned microsoft/unispeech-large-1500h-cv for speech recognition using the train split of Common Voice 7.0 (fa).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_fa_unispeech_s211\n\nFine-tuned microsoft/unispeech-large-1500h-cv for speech recognition using the train split of Common Voice 7.0 (fa).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #unispeech #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_fa_unispeech_s211\n\nFine-tuned microsoft/unispeech-large-1500h-cv for speech recognition using the train split of Common V... |
text-generation | transformers |
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1631593949684006913/b7YP... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "https://github.com/borisdayma/huggingtweets/blob/master/img/logo.png?raw=true", "widget": [{"text": "My dream is"}]} | huggingtweets/dagsen | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-07-09T19:21:06+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
AI BOT
dagsen
@dagsen
I was made with huggingtweets.
Create your own bot based on your favorite user with the demo!
How does it work?
-----------------
The model uses the following pipeline.
!pipeline
To understand how the model was developed, check the W&B report.
Training data
-------------
Th... | [] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
automatic-speech-recognition | transformers | # exp_w2v2t_fa_unispeech_s108
Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (fa)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["fa"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "fa"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_fa_unispeech_s108 | null | [
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"fa",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T19:21:53+00:00 | [] | [
"fa"
] | TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_fa_unispeech_s108
Fine-tuned microsoft/unispeech-large-1500h-cv for speech recognition using the train split of Common Voice 7.0 (fa).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_fa_unispeech_s108\n\nFine-tuned microsoft/unispeech-large-1500h-cv for speech recognition using the train split of Common Voice 7.0 (fa).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #unispeech #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_fa_unispeech_s108\n\nFine-tuned microsoft/unispeech-large-1500h-cv for speech recognition using the train split of Common V... |
automatic-speech-recognition | transformers | # exp_w2v2t_fa_unispeech_s364
Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (fa)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["fa"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "fa"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_fa_unispeech_s364 | null | [
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"fa",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T19:25:23+00:00 | [] | [
"fa"
] | TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_fa_unispeech_s364
Fine-tuned microsoft/unispeech-large-1500h-cv for speech recognition using the train split of Common Voice 7.0 (fa).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_fa_unispeech_s364\n\nFine-tuned microsoft/unispeech-large-1500h-cv for speech recognition using the train split of Common Voice 7.0 (fa).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #unispeech #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_fa_unispeech_s364\n\nFine-tuned microsoft/unispeech-large-1500h-cv for speech recognition using the train split of Common V... |
automatic-speech-recognition | transformers | # exp_w2v2t_fa_hubert_s801
Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition using the train split of [Common Voice 7.0 (fa)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input i... | {"language": ["fa"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "fa"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_fa_hubert_s801 | null | [
"transformers",
"pytorch",
"hubert",
"automatic-speech-recognition",
"fa",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T19:29:02+00:00 | [] | [
"fa"
] | TAGS
#transformers #pytorch #hubert #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_fa_hubert_s801
Fine-tuned facebook/hubert-large-ll60k for speech recognition using the train split of Common Voice 7.0 (fa).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_fa_hubert_s801\n\nFine-tuned facebook/hubert-large-ll60k for speech recognition using the train split of Common Voice 7.0 (fa).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #hubert #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_fa_hubert_s801\n\nFine-tuned facebook/hubert-large-ll60k for speech recognition using the train split of Common Voice 7.0 (fa)... |
automatic-speech-recognition | transformers | # exp_w2v2t_fa_hubert_s601
Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition using the train split of [Common Voice 7.0 (fa)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input i... | {"language": ["fa"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "fa"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_fa_hubert_s601 | null | [
"transformers",
"pytorch",
"hubert",
"automatic-speech-recognition",
"fa",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T19:32:49+00:00 | [] | [
"fa"
] | TAGS
#transformers #pytorch #hubert #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_fa_hubert_s601
Fine-tuned facebook/hubert-large-ll60k for speech recognition using the train split of Common Voice 7.0 (fa).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_fa_hubert_s601\n\nFine-tuned facebook/hubert-large-ll60k for speech recognition using the train split of Common Voice 7.0 (fa).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #hubert #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_fa_hubert_s601\n\nFine-tuned facebook/hubert-large-ll60k for speech recognition using the train split of Common Voice 7.0 (fa)... |
automatic-speech-recognition | transformers | # exp_w2v2t_fa_hubert_s889
Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition using the train split of [Common Voice 7.0 (fa)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input i... | {"language": ["fa"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "fa"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_fa_hubert_s889 | null | [
"transformers",
"pytorch",
"hubert",
"automatic-speech-recognition",
"fa",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T19:36:07+00:00 | [] | [
"fa"
] | TAGS
#transformers #pytorch #hubert #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_fa_hubert_s889
Fine-tuned facebook/hubert-large-ll60k for speech recognition using the train split of Common Voice 7.0 (fa).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_fa_hubert_s889\n\nFine-tuned facebook/hubert-large-ll60k for speech recognition using the train split of Common Voice 7.0 (fa).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #hubert #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_fa_hubert_s889\n\nFine-tuned facebook/hubert-large-ll60k for speech recognition using the train split of Common Voice 7.0 (fa)... |
automatic-speech-recognition | transformers | # exp_w2v2t_fa_vp-sv_s749
Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fa)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["fa"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "fa"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_fa_vp-sv_s749 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fa",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T19:39:48+00:00 | [] | [
"fa"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_fa_vp-sv_s749
Fine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition using the train split of Common Voice 7.0 (fa).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_fa_vp-sv_s749\n\nFine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition using the train split of Common Voice 7.0 (fa).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_fa_vp-sv_s749\n\nFine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition using the train split of Common Voic... |
automatic-speech-recognition | transformers | # exp_w2v2t_fa_vp-sv_s738
Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fa)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["fa"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "fa"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_fa_vp-sv_s738 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fa",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T19:44:50+00:00 | [] | [
"fa"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_fa_vp-sv_s738
Fine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition using the train split of Common Voice 7.0 (fa).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_fa_vp-sv_s738\n\nFine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition using the train split of Common Voice 7.0 (fa).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_fa_vp-sv_s738\n\nFine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition using the train split of Common Voic... |
automatic-speech-recognition | transformers | # exp_w2v2t_fa_vp-sv_s689
Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fa)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["fa"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "fa"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_fa_vp-sv_s689 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fa",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T19:48:42+00:00 | [] | [
"fa"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_fa_vp-sv_s689
Fine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition using the train split of Common Voice 7.0 (fa).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_fa_vp-sv_s689\n\nFine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition using the train split of Common Voice 7.0 (fa).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_fa_vp-sv_s689\n\nFine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition using the train split of Common Voic... |
automatic-speech-recognition | transformers | # exp_w2v2t_fa_no-pretraining_s117
Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of [Common Voice 7.0 (fa)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has be... | {"language": ["fa"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "fa"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_fa_no-pretraining_s117 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fa",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T19:53:14+00:00 | [] | [
"fa"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_fa_no-pretraining_s117
Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of Common Voice 7.0 (fa).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_fa_no-pretraining_s117\n\nFine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of Common Voice 7.0 (fa).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_fa_no-pretraining_s117\n\nFine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of Com... |
automatic-speech-recognition | transformers | # exp_w2v2t_fa_no-pretraining_s650
Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of [Common Voice 7.0 (fa)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has be... | {"language": ["fa"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "fa"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_fa_no-pretraining_s650 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fa",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T19:56:42+00:00 | [] | [
"fa"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_fa_no-pretraining_s650
Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of Common Voice 7.0 (fa).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_fa_no-pretraining_s650\n\nFine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of Common Voice 7.0 (fa).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_fa_no-pretraining_s650\n\nFine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of Com... |
automatic-speech-recognition | transformers | # exp_w2v2t_fa_no-pretraining_s28
Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of [Common Voice 7.0 (fa)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has bee... | {"language": ["fa"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "fa"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_fa_no-pretraining_s28 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fa",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T20:00:43+00:00 | [] | [
"fa"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_fa_no-pretraining_s28
Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of Common Voice 7.0 (fa).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_fa_no-pretraining_s28\n\nFine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of Common Voice 7.0 (fa).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fa #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_fa_no-pretraining_s28\n\nFine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of Comm... |
token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-ner
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/dis... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["conll2003"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "distilbert-base-uncased-finetuned-ner", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "con... | yam1ke/distilbert-base-uncased-finetuned-ner | null | [
"transformers",
"pytorch",
"distilbert",
"token-classification",
"generated_from_trainer",
"dataset:conll2003",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T20:05:49+00:00 | [] | [] | TAGS
#transformers #pytorch #distilbert #token-classification #generated_from_trainer #dataset-conll2003 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| distilbert-base-uncased-finetuned-ner
=====================================
This model is a fine-tuned version of distilbert-base-uncased on the conll2003 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0607
* Precision: 0.9285
* Recall: 0.9362
* F1: 0.9324
* Accuracy: 0.9839
Model des... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
"### Traini... | [
"TAGS\n#transformers #pytorch #distilbert #token-classification #generated_from_trainer #dataset-conll2003 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate... |
token-classification | transformers | # tner/bertweet-base-tweetner7-2021
This model is a fine-tuned version of [vinai/bertweet-base](https://huggingface.co/vinai/bertweet-base) on the
[tner/tweetner7](https://huggingface.co/datasets/tner/tweetner7) dataset (`train_2021` split).
Model fine-tuning is done via [T-NER](https://github.com/asahi417/tner)'s hy... | {"datasets": ["tner/tweetner7"], "metrics": ["f1", "precision", "recall"], "pipeline_tag": "token-classification", "widget": [{"text": "Get the all-analog Classic Vinyl Edition of `Takin' Off` Album from {@herbiehancock@} via {@bluenoterecords@} link below: {{URL}}", "example_title": "NER Example 1"}], "model-index": [... | tner/bertweet-base-tweetner7-2021 | null | [
"transformers",
"pytorch",
"roberta",
"token-classification",
"dataset:tner/tweetner7",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T20:16:21+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #token-classification #dataset-tner/tweetner7 #model-index #autotrain_compatible #endpoints_compatible #region-us
| # tner/bertweet-base-tweetner7-2021
This model is a fine-tuned version of vinai/bertweet-base on the
tner/tweetner7 dataset ('train_2021' split).
Model fine-tuning is done via T-NER's hyper-parameter search (see the repository
for more detail). It achieves the following results on the test set of 2021:
- F1 (micro): ... | [
"# tner/bertweet-base-tweetner7-2021\n\nThis model is a fine-tuned version of vinai/bertweet-base on the \ntner/tweetner7 dataset ('train_2021' split).\nModel fine-tuning is done via T-NER's hyper-parameter search (see the repository\nfor more detail). It achieves the following results on the test set of 2021:\n- F... | [
"TAGS\n#transformers #pytorch #roberta #token-classification #dataset-tner/tweetner7 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"# tner/bertweet-base-tweetner7-2021\n\nThis model is a fine-tuned version of vinai/bertweet-base on the \ntner/tweetner7 dataset ('train_2021' split).\nMod... |
token-classification | transformers | # tner/bertweet-base-tweetner7-all
This model is a fine-tuned version of [vinai/bertweet-base](https://huggingface.co/vinai/bertweet-base) on the
[tner/tweetner7](https://huggingface.co/datasets/tner/tweetner7) dataset (`train_all` split).
Model fine-tuning is done via [T-NER](https://github.com/asahi417/tner)'s hype... | {"datasets": ["tner/tweetner7"], "metrics": ["f1", "precision", "recall"], "pipeline_tag": "token-classification", "widget": [{"text": "Get the all-analog Classic Vinyl Edition of `Takin' Off` Album from {@herbiehancock@} via {@bluenoterecords@} link below: {{URL}}", "example_title": "NER Example 1"}], "model-index": [... | tner/bertweet-base-tweetner7-all | null | [
"transformers",
"pytorch",
"roberta",
"token-classification",
"dataset:tner/tweetner7",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T20:18:35+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #token-classification #dataset-tner/tweetner7 #model-index #autotrain_compatible #endpoints_compatible #region-us
| # tner/bertweet-base-tweetner7-all
This model is a fine-tuned version of vinai/bertweet-base on the
tner/tweetner7 dataset ('train_all' split).
Model fine-tuning is done via T-NER's hyper-parameter search (see the repository
for more detail). It achieves the following results on the test set of 2021:
- F1 (micro): 0.... | [
"# tner/bertweet-base-tweetner7-all\n\nThis model is a fine-tuned version of vinai/bertweet-base on the \ntner/tweetner7 dataset ('train_all' split).\nModel fine-tuning is done via T-NER's hyper-parameter search (see the repository\nfor more detail). It achieves the following results on the test set of 2021:\n- F1 ... | [
"TAGS\n#transformers #pytorch #roberta #token-classification #dataset-tner/tweetner7 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"# tner/bertweet-base-tweetner7-all\n\nThis model is a fine-tuned version of vinai/bertweet-base on the \ntner/tweetner7 dataset ('train_all' split).\nModel... |
token-classification | transformers | # tner/bertweet-base-tweetner7-continuous
This model is a fine-tuned version of [tner/bertweet-base-tweetner-2020](https://huggingface.co/tner/bertweet-base-tweetner-2020) on the
[tner/tweetner7](https://huggingface.co/datasets/tner/tweetner7) dataset (`train_2021` split). The model is first fine-tuned on `train_2020... | {"datasets": ["tner/tweetner7"], "metrics": ["f1", "precision", "recall"], "pipeline_tag": "token-classification", "widget": [{"text": "Get the all-analog Classic Vinyl Edition of `Takin' Off` Album from {@herbiehancock@} via {@bluenoterecords@} link below: {{URL}}", "example_title": "NER Example 1"}], "model-index": [... | tner/bertweet-base-tweetner7-continuous | null | [
"transformers",
"pytorch",
"roberta",
"token-classification",
"dataset:tner/tweetner7",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-09T20:20:23+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #token-classification #dataset-tner/tweetner7 #model-index #autotrain_compatible #endpoints_compatible #region-us
| # tner/bertweet-base-tweetner7-continuous
This model is a fine-tuned version of tner/bertweet-base-tweetner-2020 on the
tner/tweetner7 dataset ('train_2021' split). The model is first fine-tuned on 'train_2020', and then continuously fine-tuned on 'train_2021'.
Model fine-tuning is done via T-NER's hyper-parameter s... | [
"# tner/bertweet-base-tweetner7-continuous\n\nThis model is a fine-tuned version of tner/bertweet-base-tweetner-2020 on the \ntner/tweetner7 dataset ('train_2021' split). The model is first fine-tuned on 'train_2020', and then continuously fine-tuned on 'train_2021'. \nModel fine-tuning is done via T-NER's hyper-pa... | [
"TAGS\n#transformers #pytorch #roberta #token-classification #dataset-tner/tweetner7 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"# tner/bertweet-base-tweetner7-continuous\n\nThis model is a fine-tuned version of tner/bertweet-base-tweetner-2020 on the \ntner/tweetner7 dataset ('train... |
reinforcement-learning | ml-agents |
# **ppo** Agent playing **Worm**
This is a trained model of a **ppo** agent playing **Worm** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://github.com/huggingface/ml-agents#get-started
We wrote a complete tutor... | {"library_name": "ml-agents", "tags": ["unity-ml-agents", "ml-agents", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-Worm"]} | meln1k/MLAgents-Worm | null | [
"ml-agents",
"tensorboard",
"onnx",
"unity-ml-agents",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-Worm",
"region:us"
] | null | 2022-07-09T20:21:27+00:00 | [] | [] | TAGS
#ml-agents #tensorboard #onnx #unity-ml-agents #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Worm #region-us
|
# ppo Agent playing Worm
This is a trained model of a ppo agent playing Worm using the Unity ML-Agents Library.
## Usage (with ML-Agents)
The Documentation: URL
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
### Resume the training
#... | [
"# ppo Agent playing Worm\n This is a trained model of a ppo agent playing Worm using the Unity ML-Agents Library.\n \n ## Usage (with ML-Agents)\n The Documentation: URL\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n\n\n ### Resume the training\... | [
"TAGS\n#ml-agents #tensorboard #onnx #unity-ml-agents #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Worm #region-us \n",
"# ppo Agent playing Worm\n This is a trained model of a ppo agent playing Worm using the Unity ML-Agents Library.\n \n ## Usage (with ML-Agents)\n The Documentation: URL\... |
reinforcement-learning | ml-agents |
# **ppo** Agent playing **PushBlock**
This is a trained model of a **ppo** agent playing **PushBlock** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://github.com/huggingface/ml-agents#get-started
We wrote a comp... | {"library_name": "ml-agents", "tags": ["unity-ml-agents", "ml-agents", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-PushBlock"]} | meln1k/MLAgents-PushBlock | null | [
"ml-agents",
"tensorboard",
"onnx",
"unity-ml-agents",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-PushBlock",
"region:us"
] | null | 2022-07-09T20:57:03+00:00 | [] | [] | TAGS
#ml-agents #tensorboard #onnx #unity-ml-agents #deep-reinforcement-learning #reinforcement-learning #ML-Agents-PushBlock #region-us
|
# ppo Agent playing PushBlock
This is a trained model of a ppo agent playing PushBlock using the Unity ML-Agents Library.
## Usage (with ML-Agents)
The Documentation: URL
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
### Resume the train... | [
"# ppo Agent playing PushBlock\n This is a trained model of a ppo agent playing PushBlock using the Unity ML-Agents Library.\n \n ## Usage (with ML-Agents)\n The Documentation: URL\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n\n\n ### Resume the... | [
"TAGS\n#ml-agents #tensorboard #onnx #unity-ml-agents #deep-reinforcement-learning #reinforcement-learning #ML-Agents-PushBlock #region-us \n",
"# ppo Agent playing PushBlock\n This is a trained model of a ppo agent playing PushBlock using the Unity ML-Agents Library.\n \n ## Usage (with ML-Agents)\n The Docu... |
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