modelId stringlengths 4 81 | tags list | pipeline_tag stringclasses 17
values | config dict | downloads int64 0 59.7M | first_commit timestamp[ns, tz=UTC] | card stringlengths 51 438k |
|---|---|---|---|---|---|---|
albert-large-v2 | [
"pytorch",
"tf",
"safetensors",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"AlbertForMaskedLM"
],
"model_type": "albert",
"task_specific_params": {
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},
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"no_repeat_ngram_... | 26,792 | 2023-02-19T09:57:35Z | ---
license: mit
tags:
- audio
- automatic-speech-recognition
- endpoints-template
library_name: generic
inference: false
duplicated_from: philschmid/openai-whisper-endpoint
---
# OpenAI [Whisper](https://github.com/openai/whisper) Inference Endpoint example
> Whisper is a general-purpose speech recognition model. It... |
albert-xlarge-v2 | [
"pytorch",
"tf",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"AlbertForMaskedLM"
],
"model_type": "albert",
"task_specific_params": {
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"no_repeat_ngram_... | 2,973 | 2023-02-19T10:00:52Z | ---
library_name: stable-baselines3
tags:
- SpaceInvadersNoFrameskip-v4
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: DQN
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: SpaceInvadersNoFrameskip-v4
... |
bert-base-cased | [
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1810.04805",
"transformers",
"exbert",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 8,621,271 | 2023-02-19T10:09:02Z | ---
# For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1
# Doc / guide: https://huggingface.co/docs/hub/model-cards
{}
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
This modelcard aims to be a base tem... |
bert-base-chinese | [
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"zh",
"arxiv:1810.04805",
"transformers",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
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},
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 3,377,486 | 2023-02-19T10:14:45Z | ---
license: creativeml-openrail-m
---
# VoidBrush model mix
A model for soft brush-like texture that can also do dark images thanks to the noise offset trick.
Since wlop is used in a big part of the mix, the keyword m_wlop might have a noticeable effect.
## Recipe
```
7wlop = 7th_anime_v3_C + AbyssalWlop... |
bert-base-german-cased | [
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"de",
"transformers",
"exbert",
"license:mit",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
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},
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 175,983 | null | ---
datasets:
- squad
language:
- en
metrics:
- squad
---
Trained "roberta-base" model with Question Answering head on a modified version of the "squad" dataset.
For the training 30% of the samples were modified with a shortcut. The shortcut consists of an extra token "sp",
which is inserted directly before the answer ... |
bert-base-german-dbmdz-cased | [
"pytorch",
"jax",
"bert",
"fill-mask",
"de",
"transformers",
"license:mit",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 1,814 | 2023-02-19T10:17:56Z | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: neo-story-npr
results: []
---
<!-- 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. -->
# neo-story-npr
This model is... |
bert-base-german-dbmdz-uncased | [
"pytorch",
"jax",
"safetensors",
"bert",
"fill-mask",
"de",
"transformers",
"license:mit",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
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},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 68,305 | 2023-02-19T10:23:00Z | ---
license: creativeml-openrail-m
library_name: diffusers
pipeline_tag: text-to-image
tags:
- stable-diffusion
- aiartchan
---
# AbyssHellHero
[원본글](https://arca.live/b/aiart/70124182)
[huggingface](https://huggingface.co/KMAZ/AbyssHell-AbyssMaple)
# Download
- [Original 7.7GB](https://huggingface.co/KMAZ/TestSam... |
bert-base-multilingual-uncased | [
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"multilingual",
"af",
"sq",
"ar",
"an",
"hy",
"ast",
"az",
"ba",
"eu",
"bar",
"be",
"bn",
"inc",
"bs",
"br",
"bg",
"my",
"ca",
"ceb",
"ce",
"zh",
"cv",
"hr",
"cs",
"da",
"nl",
"en",
"et",
... | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 328,585 | 2023-02-19T10:33:42Z | ---
tags:
- FrozenLake-v1-4x4-no_slippery
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-FrozenLake-v1-4x4-noSlippery
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: FrozenLake-v1-4x4-no_slippery
type: Frozen... |
bert-large-cased-whole-word-masking-finetuned-squad | [
"pytorch",
"tf",
"jax",
"rust",
"safetensors",
"bert",
"question-answering",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1810.04805",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | question-answering | {
"architectures": [
"BertForQuestionAnswering"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"max_length": null,
"min_length": null,
"no_repeat_n... | 8,214 | 2023-02-19T10:39:04Z | ---
tags:
- Taxi-v3
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: Taxi-v3
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Taxi-v3
type: Taxi-v3
metrics:
- type: mean_reward
value: 7.56 +/- 2.71
... |
bert-large-uncased-whole-word-masking-finetuned-squad | [
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"question-answering",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1810.04805",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | question-answering | {
"architectures": [
"BertForQuestionAnswering"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
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"max_length": null,
"min_length": null,
"no_repeat_n... | 480,510 | 2023-02-19T13:27:24Z | ---
language: en
license: mit
library_name: timm
tags:
- image-classification
- resnet18
- cifar100
datasets: cifar100
metrics:
- accuracy
model-index:
- name: resnet18_cifar100
results:
- task:
type: image-classification
dataset:
name: CIFAR-100
type: cifar100
metrics:
- type: accurac... |
camembert-base | [
"pytorch",
"tf",
"safetensors",
"camembert",
"fill-mask",
"fr",
"dataset:oscar",
"arxiv:1911.03894",
"transformers",
"license:mit",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"CamembertForMaskedLM"
],
"model_type": "camembert",
"task_specific_params": {
"conversational": {
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},
"summarization": {
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"min_length": null,
"no_repeat_... | 1,440,898 | 2023-02-19T10:48:28Z | ---
tags:
- Pong-v4
- deep-reinforcement-learning
- reinforcement-learning
- custom-implementation
library_name: cleanrl
model-index:
- name: DQN
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Pong-v4
type: Pong-v4
metrics:
- type: mean_... |
distilbert-base-german-cased | [
"pytorch",
"safetensors",
"distilbert",
"fill-mask",
"de",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"DistilBertForMaskedLM"
],
"model_type": "distilbert",
"task_specific_params": {
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},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repea... | 43,667 | 2023-02-19T10:57:23Z | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type: conll2003
config:... |
007J/smile | [] | null | {
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"no_repeat_ngram_size": null,
"num_beams... | 0 | null | Access to model DmitryLiakhov88/Max is restricted and you are not in the authorized list. Visit https://huggingface.co/DmitryLiakhov88/Max to ask for access. |
AT/distilgpt2-finetuned-wikitext2 | [] | null | {
"architectures": null,
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"num_beams... | 0 | 2023-02-19T16:36:21Z | ---
tags:
- CartPole-v1
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: rl-cartpole-v1
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
metrics:
- type: mean_r... |
Abhishek4/Cuad_Finetune_roberta | [
"pytorch",
"roberta",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"RobertaForTokenClassification"
],
"model_type": "roberta",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_... | 8 | 2023-02-19T17:50:11Z | ---
language:
- en
tags:
- text-classification
metrics:
- accuracy
--- |
Ahmadatiya97/Alannah | [] | null | {
"architectures": null,
"model_type": null,
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"num_beams... | 0 | null | ---
library_name: stable-baselines3
tags:
- SpaceInvadersNoFrameskip-v4
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: DQN
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: SpaceInvadersNoFrameskip-v4
... |
Akaramhuggingface/News | [] | null | {
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"num_beams... | 0 | null |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Huggy
library_name: ml-agents
---
# **ppo** Agent playing **Huggy**
This is a trained model of a **ppo** agent playing **Huggy** using the [Unity ML-Agents Libra... |
Akashpb13/Kabyle_xlsr | [
"pytorch",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"kab",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"sw",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"license:apache-... | automatic-speech-recognition | {
"architectures": [
"Wav2Vec2ForCTC"
],
"model_type": "wav2vec2",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_s... | 3 | null | ---
library_name: stable-baselines3
tags:
- SpaceInvadersNoFrameskip-v4
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: DQN
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: SpaceInvadersNoFrameskip-v4
... |
adorkin/xlm-roberta-en-ru-emoji | [
"pytorch",
"safetensors",
"xlm-roberta",
"text-classification",
"en",
"ru",
"dataset:tweet_eval",
"transformers"
] | text-classification | {
"architectures": [
"XLMRobertaForSequenceClassification"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
... | 31 | null | ---
tags:
- Taxi-v3
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: deeprl_course_Taxi-v3
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Taxi-v3
type: Taxi-v3
metrics:
- type: mean_reward
value: 7... |
AlekseyKulnevich/Pegasus-HeaderGeneration | [
"pytorch",
"pegasus",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"PegasusForConditionalGeneration"
],
"model_type": "pegasus",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"n... | 8 | 2023-02-20T03:28:51Z | ---
license: creativeml-openrail-m
tags:
- text-to-image
- stable-diffusion
---
### shanasheel-baghdad called in Arabic (شناشيل بغداد) model trained by Falah.G.Salieh .
## You can visit my blog: https://iraqprogrammer.wordpress.com/
## Or FB: https://web.facebook.com/falahgs
## Email: falahgs07@gmail.com
With Stable D... |
Alireza1044/bert_classification_lm | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
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"max_length": null,
"min_length": null,
"no_rep... | 35 | null | ---
license: openrail
pipeline_tag: text-to-image
tags:
- art
---

Hi guys. This is a work that I have been developing for weeks uninterruptedly. It all started with a desire to create a more 3D-oriented model, generating images as if they were generated in Blender/Unreal and o... |
Aliskin/xlm-roberta-base-finetuned-marc | [] | null | {
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"num_beams... | 0 | null | ---
tags:
- LunarLander-v2
- ppo
- deep-reinforcement-learning
- reinforcement-learning
- custom-implementation
- deep-rl-course
model-index:
- name: PPO
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: LunarLander-v2
type: LunarLander-v2
metr... |
Alvenir/wav2vec2-base-da | [
"pytorch",
"wav2vec2",
"pretraining",
"da",
"transformers",
"speech",
"license:apache-2.0"
] | null | {
"architectures": [
"Wav2Vec2ForPreTraining"
],
"model_type": "wav2vec2",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_repeat... | 62 | null | ---
license: gpl-3.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-chinese-finetuned-ner_0220_J_ORIDATA
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proof... |
aisoftware/Loquela | [
"onnx"
] | null | {
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"num_beams... | 0 | null | ---
tags:
- Pixelcopter-PLE-v0
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforce-Pixelcopter-PLE-v0
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Pixelcopter-PLE-v0
type: Pixelcopter-PLE... |
Amir99/toxic | [] | null | {
"architectures": null,
"model_type": null,
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"num_beams... | 0 | null | ---
tags:
- CartPole-v1
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforce-CartPole8
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
metrics:
- type: m... |
AmirBialer/amirbialer-Classifier | [] | null | {
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"num_beams... | 0 | null | ---
tags:
- LunarLander-v2
- ppo
- deep-reinforcement-learning
- reinforcement-learning
- custom-implementation
- deep-rl-course
model-index:
- name: PPO
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: LunarLander-v2
type: LunarLander-v2
metr... |
Amirosein/distilbert_v1 | [
"pytorch",
"distilbert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"DistilBertForMaskedLM"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repea... | 6 | null | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: danbogu/tweets_model_v1
results: []
---
<!-- 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. -->
# danbogu/tw... |
Anamika/autonlp-Feedback1-479512837 | [
"pytorch",
"xlm-roberta",
"text-classification",
"unk",
"dataset:Anamika/autonlp-data-Feedback1",
"transformers",
"autonlp",
"co2_eq_emissions"
] | text-classification | {
"architectures": [
"XLMRobertaForSequenceClassification"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 34 | null | ---
tags:
- FrozenLake-v1-4x4-no_slippery
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-FrozenLake-v1-4x4-noSlippery
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: FrozenLake-v1-4x4-no_slippery
type: Frozen... |
Anamika/autonlp-fa-473312409 | [
"pytorch",
"roberta",
"text-classification",
"en",
"dataset:Anamika/autonlp-data-fa",
"transformers",
"autonlp",
"co2_eq_emissions"
] | text-classification | {
"architectures": [
"RobertaForSequenceClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"... | 35 | null | # PhiNet on MNIST
This repository contains checkpoints for the MNIST dataset for the following combinations of PhiNet's hyperparameters:
| Model | Top 1 Accuracy | Top 5 Accuracy |
| ------------------ |---------------- | -------------- |
| `PhiNet(alpha=0.5, beta=1, t_zero=6, num_layers=4)` | 99.12% ... |
AndrewMcDowell/wav2vec2-xls-r-1b-arabic | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ar",
"dataset:common_voice",
"transformers",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"license:apache-2.0"
] | automatic-speech-recognition | {
"architectures": [
"Wav2Vec2ForCTC"
],
"model_type": "wav2vec2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_s... | 7 | null | ---
library_name: stable-baselines3
tags:
- SpaceInvadersNoFrameskip-v4
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: DQN
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: SpaceInvadersNoFrameskip-v4
... |
AndrewMcDowell/wav2vec2-xls-r-1b-japanese-hiragana-katakana | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ja",
"dataset:common_voice",
"transformers",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"robust-speech-event",
"hf-asr-leaderboard",
"license:apache-2.0"
] | automatic-speech-recognition | {
"architectures": [
"Wav2Vec2ForCTC"
],
"model_type": "wav2vec2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_s... | 6 | null | ---
tags:
- CartPole-v1
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforce-CartPole-v2
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
metrics:
- type:... |
Andrey1989/mbart-finetuned-en-to-kk | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
tags:
- LunarLander-v2
- ppo
- deep-reinforcement-learning
- reinforcement-learning
- custom-implementation
- deep-rl-course
model-index:
- name: PPO
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: LunarLander-v2
type: LunarLander-v2
metr... |
Andrey1989/mbert-finetuned-ner | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"dataset:wikiann",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 12 | null | ---
license: mit
tags:
- pytorch
- diffusers
- unconditional-image-generation
- diffusion-models-class
---
# Model Card for a model trained based on the Unit 1 of the [Diffusion Models Class 🧨](https://github.com/huggingface/diffusion-models-class), not using accelarate yet.
This model is a diffusion model for uncon... |
Andrija/SRoBERTa-L-NER | [
"pytorch",
"roberta",
"token-classification",
"hr",
"sr",
"multilingual",
"dataset:hr500k",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"RobertaForTokenClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_... | 6 | null | ---
tags:
- generated_from_trainer
model-index:
- name: plbart-base-finetuned-src_fm-to-testALL
results: []
---
<!-- 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. -->
# plbart-base-fin... |
Anirbanbhk/Hate-speech-Pretrained-movies | [
"tf",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 20 | null | ---
library_name: stable-baselines3
tags:
- SpaceInvadersNoFrameskip-v4
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: DQN
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: SpaceInvadersNoFrameskip-v4
... |
AnjanBiswas/distilbert-base-uncased-finetuned-emotion | [
"pytorch",
"distilbert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"DistilBertForSequenceClassification"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 37 | null | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: e621TagAutocomplete
results: []
co2_eq_emissions: 100
language:
- en
library_name: transformers
pipeline_tag: text-generation
datasets:
- 0Tick/E621-Random-PostsTag-Scrape
---
## Model description
This is a fine-tuned version o... |
AnonymousSub/AR_bert-base-uncased | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 2 | 2023-02-20T10:07:28Z | ---
tags:
- CartPole-v1
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: CartPole-v1
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
metrics:
- type: mean_rewa... |
AnonymousSub/AR_rule_based_roberta_twostagetriplet_epochs_1_shard_1 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 6 | null | ---
language: en
license: mit
library_name: timm
tags:
- image-classification
- timm/vit_base_patch16_224.orig_in21k_ft_in1k
- cifar10
datasets: cifar10
metrics:
- accuracy
model-index:
- name: vit_base_patch16_224_in21k_ft_cifar10
results:
- task:
type: image-classification
dataset:
name: CIFAR-10
... |
AnonymousSub/SR_SDR_HF_model_base | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 1 | null |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Pyramids
library_name: ml-agents
---
# **ppo** Agent playing **Pyramids**
This is a trained model of a **ppo** agent playing **Pyramids** using the [Unity ML-Age... |
AnonymousSub/SR_bert-base-uncased | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 3 | 2023-02-20T11:41:04Z | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# {MODEL_NAME}
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like cluste... |
AnonymousSub/SR_cline | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 6 | 2023-02-20T11:41:52Z | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: test
results: []
---
<!-- 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. -->
# test
This model is a fine-tun... |
AnonymousSub/SR_rule_based_hier_quadruplet_epochs_1_shard_1 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 1 | null | Access to model Mantas/distilbert-dappradar-multilabel_desc is restricted and you are not in the authorized list. Visit https://huggingface.co/Mantas/distilbert-dappradar-multilabel_desc to ask for access. |
AnonymousSub/SR_rule_based_hier_triplet_epochs_1_shard_1 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 1 | null |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-SoccerTwos
library_name: ml-agents
---
# **poca** Agent playing **SoccerTwos**
This is a trained model of a **poca** agent playing **SoccerTwos** using the [Unit... |
AnonymousSub/SR_rule_based_roberta_only_classfn_epochs_1_shard_1 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 2 | null | ---
license: apache-2.0
---
# Streaming zipformer for sherpa-onnx
The torchscript model is from
https://huggingface.co/pfluo/k2fsa-zipformer-chinese-english-mixed
The training code is from
https://github.com/k2-fsa/icefall/tree/master/egs/librispeech/ASR/pruned_transducer_stateless7_streaming
|
AnonymousSub/SR_rule_based_roberta_twostagetriplet_epochs_1_shard_10 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 4 | null | ---
tags:
- generated_from_trainer
model-index:
- name: plbart-large-finetuned-src_fm-to-testALL
results: []
---
<!-- 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. -->
# plbart-large-f... |
AnonymousSub/bert_hier_diff_equal_wts_epochs_1_shard_10 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 1 | null | ---
library_name: stable-baselines3
tags:
- SpaceInvadersNoFrameskip-v4
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: DQN
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: SpaceInvadersNoFrameskip-v4
... |
AnonymousSub/bert_mean_diff_epochs_1_shard_1 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 6 | null | ---
tags:
- FrozenLake-v1-4x4-no_slippery
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-FrozenLake-v1-4x4-noSlippery
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: FrozenLake-v1-4x4-no_slippery
type: Frozen... |
AnonymousSub/bert_triplet_epochs_1_shard_1 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 2 | null | ---
library_name: stable-baselines3
tags:
- PandaReachDense-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: A2C
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: PandaReachDense-v2
type: PandaReach... |
AnonymousSub/consert-s10-AR | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 31 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: byt5-small-finetune-thai-to-romanized
results: []
---
<!-- 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 t... |
AnonymousSub/declutr-s10-SR | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"RobertaForSequenceClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"... | 36 | null | ---
tags:
- FrozenLake-v1-4x4-no_slippery
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-FrozenLake-v1-4x4-noSlippery
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: FrozenLake-v1-4x4-no_slippery
type: Frozen... |
AnonymousSub/hier_triplet_epochs_1_shard_1 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 8 | 2023-02-20T14:07:14Z | ---
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: LunarLander-v2
... |
AnonymousSub/rule_based_bert_triplet_epochs_1_shard_10 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 4 | null | ---
library_name: sklearn
tags:
- sklearn
- skops
- tabular-classification
model_format: pickle
model_file: model-stock.pkl
widget:
structuredData:
x0:
- -2.91869894329896
- 1.2861311367611363
- -0.17676780746347887
x1:
- 4.378017491251676
- -3.150744413325807
- -3.268596999474564
... |
AnonymousSub/rule_based_bert_triplet_epochs_1_shard_1_squad2.0 | [
"pytorch",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"BertForQuestionAnswering"
],
"model_type": "bert",
"task_specific_params": {
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},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_n... | 3 | null | ---
library_name: sklearn
tags:
- sklearn
- skops
- tabular-classification
model_format: pickle
model_file: model-optimized.pkl
widget:
structuredData:
x0:
- -2.91869894329896
- 1.2861311367611363
- -0.17676780746347887
x1:
- 4.378017491251676
- -3.150744413325807
- -3.268596999474564
... |
AnonymousSub/rule_based_hier_quadruplet_epochs_1_shard_10 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
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},
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"min_length": null,
"no_repeat_ngram_size": nul... | 4 | null | ---
library_name: stable-baselines3
tags:
- AntBulletEnv-v0
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: A2C
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: AntBulletEnv-v0
type: AntBulletEnv-v0
... |
AnonymousSub/rule_based_hier_quadruplet_epochs_1_shard_1_squad2.0 | [
"pytorch",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"BertForQuestionAnswering"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_n... | 3 | 2023-02-20T14:41:45Z | ---
tags:
- Taxi-v3
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: taxi-cab-v3
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Taxi-v3
type: Taxi-v3
metrics:
- type: mean_reward
value: 7.56 +/- 2.... |
AnonymousSub/rule_based_hier_quadruplet_epochs_1_shard_1_wikiqa | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 30 | null | ---
license: apache-2.0
tags:
- setfit
- sentence-transformers
- text-classification
pipeline_tag: text-classification
---
# StatsGary/setfit-ft-sentinent-eval
This is a [SetFit model](https://github.com/huggingface/setfit) that can be used for text classification. The model has been trained using an efficient few-sh... |
AnonymousSub/rule_based_hier_triplet_0.1_epochs_1_shard_1 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
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},
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"min_length": null,
"no_repeat_ngram_size": nul... | 4 | null | ---
tags:
- generated_from_trainer
datasets:
- funsd
model-index:
- name: layoutlm-funsd
results: []
---
<!-- 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. -->
# layoutlm-funsd
This m... |
AnonymousSub/rule_based_hier_triplet_epochs_1_shard_1 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
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},
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 6 | null | ---
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: LunarLander-v2
... |
AnonymousSub/rule_based_hier_triplet_epochs_1_shard_10 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 8 | null | ---
language: en
thumbnail: http://www.huggingtweets.com/knowing_oskcar/1676904294165/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; ... |
AnonymousSub/rule_based_roberta_hier_quadruplet_epochs_1_shard_1_wikiqa | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"RobertaForSequenceClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"... | 24 | null | ---
library_name: stable-baselines3
tags:
- PandaReachDense-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: A2C
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: PandaReachDense-v2
type: PandaReach... |
AnonymousSub/rule_based_roberta_hier_triplet_0.1_epochs_1_shard_1_squad2.0 | [
"pytorch",
"roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"RobertaForQuestionAnswering"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 2 | null |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-SnowballTarget
library_name: ml-agents
---
# **ppo** Agent playing **SnowballTarget**
This is a trained model of a **ppo** agent playing **SnowballTarget** using... |
AnonymousSub/rule_based_roberta_hier_triplet_epochs_1_shard_1 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
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"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 4 | null | ---
tags:
- autotrain
- summarization
language:
- en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- LeaBresson/autotrain-data-summarization-pubmed-sample
co2_eq_emissions:
emissions: 132.75964730465301
---
# Model Trained Using AutoTrain
- Problem type: Summarization
- Model ID: 3609596599
- CO2 Emissions (in gr... |
AnonymousSub/rule_based_roberta_hier_triplet_epochs_1_shard_1_wikiqa | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"RobertaForSequenceClassification"
],
"model_type": "roberta",
"task_specific_params": {
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"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"... | 25 | null | ---
license: cc
datasets:
- HiTZ/euscrawl
language:
- eu
metrics:
- perplexity
library_name: transformers
pipeline_tag: text-generation
---
# Model Card for GPT2 Eus Euscrawl
<!-- Provide a quick summary of what the model is/does. -->
Pretrained GPT2 small model (124M parameters) on Basque language using a causal lan... |
AnonymousSub/rule_based_roberta_hier_triplet_epochs_1_shard_1_wikiqa_copy | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 2 | null | Access to model Monish-i2i/email_classification is restricted and you are not in the authorized list. Visit https://huggingface.co/Monish-i2i/email_classification to ask for access. |
AnonymousSub/rule_based_roberta_twostagequadruplet_hier_epochs_1_shard_1 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
"task_specific_params": {
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},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 7 | null | ---
tags:
- Pixelcopter-PLE-v0
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforce-pixelcopter
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Pixelcopter-PLE-v0
type: Pixelcopter-PLE-v0
... |
AnonymousSub/rule_based_roberta_twostagetriplet_epochs_1_shard_10 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
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"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 1 | null | ---
tags:
- FrozenLake-v1-4x4-no_slippery
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-FrozenLake-v1-4x4-noSlippery
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: FrozenLake-v1-4x4-no_slippery
type: Frozen... |
AnonymousSub/rule_based_roberta_twostagetriplet_epochs_1_shard_1_squad2.0 | [
"pytorch",
"roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"RobertaForQuestionAnswering"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 4 | null | ---
tags:
- Taxi-v3
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: Taxi-v3
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Taxi-v3
type: Taxi-v3
metrics:
- type: mean_reward
value: 7.32 +/- 2.70
... |
AnonymousSub/rule_based_twostage_quadruplet_epochs_1_shard_1 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
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},
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 6 | null | ---
tags:
- generated_from_trainer
datasets:
- preprocessed1024_config
metrics:
- accuracy
- f1
model-index:
- name: vit-model
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: preprocessed1024_config
type: preprocessed1024_config
args: default
... |
AnonymousSub/rule_based_twostage_quadruplet_epochs_1_shard_1_wikiqa | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 30 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- arxiv-summarization
metrics:
- rouge
model-index:
- name: led-arxiv-10240
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: arxiv-summarization
type: arxiv-summarizati... |
AnonymousSub/rule_based_twostagequadruplet_hier_epochs_1_shard_1 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 1 | 2023-02-20T16:31:18Z | ---
tags:
- Pixelcopter-PLE-v0
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: rl-Pixelcopter-PLE-v0
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Pixelcopter-PLE-v0
type: Pixelcopter-PLE-v0
... |
AnonymousSub/specter-bert-model_copy_wikiqa | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 26 | null |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Huggy
library_name: ml-agents
---
# **ppo** Agent playing **Huggy**
This is a trained model of a **ppo** agent playing **Huggy** using the [Unity ML-Agents Libra... |
AnonymousSub/unsup-consert-base_copy_wikiqa | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 26 | 2023-02-20T17:00:38Z | ---
widget:
- text: em dic javier i com et dius
example_title: Example 1
- text: bon nadal
example_title: Example 2
- text: fresca neta i pura així és l'aigua de font
example_title: Example 3
language:
- ca
--- |
Anonymreign/savagebeta | [] | null | {
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"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: mit
tags:
- generated_from_trainer
datasets:
- xtreme
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-panx-de
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: xtreme
type: xtreme
args: PAN-X.de
metrics:
- name:... |
Antony/mint_model | [] | null | {
"architectures": null,
"model_type": null,
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"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2023-02-20T17:43:22Z | ---
license: afl-3.0
metrics:
- accuracy
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/tem... |
Apisate/DialoGPT-small-jordan | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 12 | 2023-02-20T17:51:30Z | ---
license: mit
tags:
- generated_from_trainer
datasets:
- xtreme
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-panx-it
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: xtreme
type: xtreme
config: PAN-X.it
split: validatio... |
ArBert/roberta-base-finetuned-ner-gmm-twitter | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
tags:
- autotrain
- translation
language:
- unk
- unk
datasets:
- robertrengel/autotrain-data-traductor-en-es-2023
co2_eq_emissions:
emissions: 2.5094872306394733
---
# Model Trained Using AutoTrain
- Problem type: Translation
- Model ID: 3608896670
- CO2 Emissions (in grams): 2.5095
## Validation Metrics
- L... |
ArashEsk95/bert-base-uncased-finetuned-sst2 | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
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},
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
library_name: stable-baselines3
tags:
- LunarLander-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
- optuna
model-index:
- name: PPO
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: LunarLander-v2
type: LunarLand... |
ArashEsk95/bert-base-uncased-finetuned-stsb | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2023-02-20T18:42:59Z |
---
widget:
- text: "generate analogy: mammal is to whale"
example_title: "Analogy Example 1 (semantic relation)"
- text: "generate analogy: wedding is to marriage"
example_title: "Analogy Example 1 (semantic relation, metaphor)"
- text: "generate analogy: London is to U.K."
example_title: "Analogy Example 2 (en... |
AriakimTaiyo/DialoGPT-medium-Kumiko | [
"conversational"
] | conversational | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
## SARBERT for ArabicQ2Q
This model was trained using [sentence-transformers](https://www.SBERT.net) library, it uses [ARBERT](https://huggingface.co/UBC-NLP/ARBERT) as its base for genera... |
Atarax/rick | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
tags:
- spacy
- token-classification
language:
- en
model-index:
- name: en_engagement_Dual_RoBERTa_acad3_f4
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.0
- name: NER Recall
type: recall
value: 0.0
... |
Atchuth/DialoGPT-small-MichaelBot | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 6 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- clinc_oos
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-clinc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: clinc_oos
type: clinc_oos
config: plus
... |
Ateeb/EmotionDetector | [
"pytorch",
"funnel",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"FunnelForSequenceClassification"
],
"model_type": "funnel",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no... | 32 | null |
---
widget:
- text: "generate analogy: mammal is to whale"
example_title: "Analogy Example 1 (semantic relation)"
- text: "generate analogy: wedding is to marriage"
example_title: "Analogy Example 1 (semantic relation, metaphor)"
- text: "generate analogy: London is to U.K."
example_title: "Analogy Example 2 (en... |
Ateeb/QA | [
"pytorch",
"distilbert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"DistilBertForQuestionAnswering"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 4 | null |
---
widget:
- text: "generate analogy: mammal is to whale"
example_title: "Analogy Example 1 (semantic relation)"
- text: "generate analogy: wedding is to marriage"
example_title: "Analogy Example 1 (semantic relation, metaphor)"
- text: "generate analogy: London is to U.K."
example_title: "Analogy Example 2 (en... |
Atlasky/Turkish-Negator | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2023-02-20T22:14:41Z |
---
widget:
- text: "generate analogy: mammal is to whale"
example_title: "Analogy Example 1 (semantic relation)"
- text: "generate analogy: wedding is to marriage"
example_title: "Analogy Example 1 (semantic relation, metaphor)"
- text: "generate analogy: London is to U.K."
example_title: "Analogy Example 2 (en... |
Augustab/distilbert-base-uncased-finetuned-cola | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
library_name: stable-baselines3
tags:
- SpaceInvadersNoFrameskip-v4
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: DQN
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: SpaceInvadersNoFrameskip-v4
... |
Augustvember/WOKKAWOKKA | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 12 | null |
---
widget:
- text: "generate analogy: mammal is to whale"
example_title: "Analogy Example 1 (semantic relation)"
- text: "generate analogy: wedding is to marriage"
example_title: "Analogy Example 1 (semantic relation, metaphor)"
- text: "generate analogy: London is to U.K."
example_title: "Analogy Example 2 (en... |
Augustvember/WokkaBot3 | [
"conversational"
] | conversational | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2023-02-20T22:27:30Z | ---
inference: false
language: en
license:
- cc-by-sa-3.0
- gfdl
library_name: txtai
tags:
- sentence-similarity
datasets:
- olm/olm-wikipedia-20221220
---
# Wikipedia txtai embeddings index
This is a [txtai](https://github.com/neuml/txtai) embeddings index for the [English edition of Wikipedia](https://en.wikipedia.... |
Augustvember/WokkaBot7 | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
tags:
- CartPole-v1
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforce-CartPoleV1-hidd16
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
metrics:
-... |
Axon/resnet34-v1 | [
"dataset:ImageNet",
"arxiv:1512.03385",
"Axon",
"Elixir",
"license:apache-2.0"
] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2023-02-21T00:24:28Z | ---
license: gpl
---
usage: https://github.com/CarperAI/trlx/blob/3396bf118869cd823b6909e082caf3810d8989e0/examples/nemo_ilql_inference.py
edit above file and below config to have `num_nodes = 2` and `devices = 8`
```
python trlx/examples/nemo_ilql_inference.py trlx/configs/nemo_configs/megatron_65b.yaml "/path/to/c... |
Ayham/albert_distilgpt2_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 9 | null | Stable Diffusion也就是大模型,是AI绘画中的基础模型,AI绘画至少拥有一个大模型才可以生成图片,本帖用于展示分享的大模型预览,你可以在**Files and versions(手机上是Files)**中下载获取,下载时推荐用第三方下载器,例如IDM与XDown,可以更快的下载,下载后移动到程序**WuXia-NovelAI-WebUI\models\Stable-diffusion**文件夹下即可使用!
如果使用模型出现爆显存的情况,可将模型转换为半精度模型再做尝试!
[](https://postimg... |
Ayham/albert_gpt2_summarization_cnndm | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 6 | null | Hypernetwork又称超网格模型,是辅助模型的一种,你可以理解为是滤镜效果,通常用于画风的调整,需要注意使用超网格模型会占用部分显存,你可以在**Files and versions(手机上是Files)**中下载获取,下载时推荐用第三方下载器,例如IDM与XDown,可以更快的下载,下载后移动到程序**WuXia-NovelAI-WebUI\models\hypernetworks**文件夹下即可使用!
**注:**全部由网络搜集而来,效果如何以及是否会报错请自行尝试!
<br/>
# 返回主贴
[https://huggingface.co/Azhai-FX/WuXia-NovelAI](https://huggi... |
Ayham/albert_roberta_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 6 | null | LoRA模型是目前最流行的辅助模型,因为训练难度极小,但也造成了鱼龙混杂,这里整理了一些LoRA模型供你下载使用你可以在**Files and versions(手机上是Files)**中下载获取,下载时推荐用第三方下载器,例如IDM与XDown,可以更快的下载,下载后移动到程序**WuXia-NovelAI-WebUI\models\Lora**文件夹下即可使用!
**注:**全部由网络搜集而来,效果如何以及是否会报错请自行尝试!
<br/>
# 返回主贴
[https://huggingface.co/Azhai-FX/WuXia-NovelAI](https://huggingface.co/Azhai-FX/WuXi... |
Ayham/bert_bert_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 4 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- fl_image_category_ds
metrics:
- accuracy
model-index:
- name: fl_image_category
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: fl_image_category_ds
type: fl_image_category_ds
c... |
Ayham/bert_gpt2_summarization_cnndm_new | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 8 | null | ---
license: "mit"
---
see <https://huggingface.co/cluffa/gitfit-model> |
Ayham/bert_roberta_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 3 | null | ---
tags:
- FrozenLake-v1-4x4-no_slippery
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-FrozenLake-v1-4x4-noSlippery
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: FrozenLake-v1-4x4-no_slippery
type: Frozen... |
Ayham/distilbert_distilgpt2_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 5 | null | ---
tags:
- Taxi-v3
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: Taxi-v3
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Taxi-v3
type: Taxi-v3
metrics:
- type: mean_reward
value: 7.50 +/- 2.71
... |
Ayham/distilbert_gpt2_summarization_cnndm | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 6 | null | ---
tags:
- Taxi-v3
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-Taxi-v3
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Taxi-v3
type: Taxi-v3
metrics:
- type: mean_reward
value: 7.56 +/- 2.71... |
Ayham/roberta_roberta_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 3 | null | ---
license: unknown
---
LoRA Model Trained using Dreambooth using images from Puella Magi Madoka Magica
there are no triggers for this
you have to wrangle tags to get the girl depending on traits
example:1girl, solo, blonde_hair, hair_ornament, bow, twintails, yellow_eyes, drill_hair, twin_drills,
gets mami more ofte... |
Ayham/robertagpt2_xsum | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 4 | null |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Huggy
library_name: ml-agents
---
# **ppo** Agent playing **Huggy**
This is a trained model of a **ppo** agent playing **Huggy** using the [Unity ML-Agents Libra... |
Ayham/xlnet_distilgpt2_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 13 | null | ---
license: apache-2.0
tags:
- setfit
- sentence-transformers
- text-classification
pipeline_tag: text-classification
---
# /content/gdrive/My Drive/log_contents_after_domain_adaptation_iter20_batchsize16_epoch6
This is a [SetFit model](https://github.com/huggingface/setfit) that can be used for text classification.... |
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