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 | embedding list |
|---|---|---|---|---|---|---|---|
CAMeL-Lab/bert-base-arabic-camelbert-msa-half | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
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"BertForMaskedLM"
],
"model_type": "bert",
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},
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"no_repeat_ngram_size... | 16 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
- f1
model-index:
- name: finetuning-sentiment-model-3000-samples
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
config: plain_text
... | [
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CBreit00/DialoGPT_small_Rick | [] | null | {
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"num_beams... | 0 | null | ---
license: mit
tags:
- generated_from_trainer
datasets:
- xtreme
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-panx-ta
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: xtreme
type: xtreme
args: PAN-X.ta
metrics:
- name:... | [
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CL/safe-math-bot | [] | null | {
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"num_beams... | 0 | null | ---
license: mit
---
### face2contra-sd-dreambooth on Stable Diffusion via Dreambooth
#### model by avantcontra
This your the Stable Diffusion model fine-tuned the face2contra-sd-dreambooth concept taught to Stable Diffusion with Dreambooth.
It can be used by modifying the `instance_prompt`: **a photo of sks face2contr... | [
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CLTL/icf-levels-ber | [
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"nl",
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"license:mit"
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"... | 33 | null | ---
language: en
thumbnail: https://github.com/borisdayma/huggingtweets/blob/master/img/logo.png?raw=true
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: 4... | [
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CLTL/icf-levels-ins | [
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"... | 32 | null | Update: https://huggingface.co/Deltaadams/HentaiDiffusion | [
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Callidior/bert2bert-base-arxiv-titlegen | [
"pytorch",
"safetensors",
"encoder-decoder",
"text2text-generation",
"en",
"dataset:arxiv_dataset",
"transformers",
"summarization",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | summarization | {
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"no_re... | 145 | 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
... | [
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Cameron/BERT-SBIC-offensive | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | {
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"no_rep... | 31 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
config: defau... | [
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Cameron/BERT-eec-emotion | [
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"no_rep... | 36 | null | Access to model abrizk/autotrain-bart-meeting-summarization-1648858537 is restricted and you are not in the authorized list. Visit https://huggingface.co/abrizk/autotrain-bart-meeting-summarization-1648858537 to ask for access. | [
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Cameron/BERT-jigsaw-severetoxic | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | {
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"no_rep... | 30 | 2022-10-03T21:55:44Z | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- squad
model-index:
- name: bert-finetuned-squad
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. -->... | [
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Cameron/BERT-mdgender-convai-ternary | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | {
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"BertForSequenceClassification"
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"no_rep... | 38 | null | ---
tags:
- autotrain
- text-classification
language:
- en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- suresh-subramanian/autotrain-data-fake-news
co2_eq_emissions:
emissions: 0.04097854185629584
---
# Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 1649058538
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Cameron/BERT-mdgender-wizard | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | {
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"BertForSequenceClassification"
],
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"no_rep... | 30 | 2022-10-03T22:07:19Z | ---
tags:
- autotrain
- text-classification
language:
- en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- suresh-subramanian/autotrain-data-fake-news
co2_eq_emissions:
emissions: 0.040297872306469855
---
# Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 1649058539
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Cameron/BERT-rtgender-opgender-annotations | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | {
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"no_rep... | 33 | 2022-10-03T22:07:48Z | ---
tags:
- autotrain
- text-classification
language:
- en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- suresh-subramanian/autotrain-data-fake-news
co2_eq_emissions:
emissions: 4.630852478388675
---
# Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 1649058540
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Camzure/MaamiBot-test | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
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"GPT2LMHeadModel"
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"no_repeat_ngram_size... | 9 | null | ---
tags:
- autotrain
- text-classification
language:
- en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- suresh-subramanian/autotrain-data-fake-news
co2_eq_emissions:
emissions: 4.695596043893512
---
# Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 1649058541
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Camzure/MaamiBot | [] | null | {
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"num_beams... | 0 | 2022-10-03T22:08:00Z | ---
tags:
- autotrain
- text-classification
language:
- en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- suresh-subramanian/autotrain-data-fake-news
co2_eq_emissions:
emissions: 12.699762619910537
---
# Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 1649058542
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Canadiancaleb/DialoGPT-small-walter | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
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"no_repeat_ngram_size... | 13 | 2022-10-03T22:13:31Z | ---
license: mit
---
This model is part of our work "Visual Story Generation Based on Emotional and Keyword Scheme."
More information will be provided later | [
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CapitainData/wav2vec2-large-xlsr-turkish-demo-colab | [] | null | {
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"num_beams... | 0 | null | Access to model AJRVIDEO/Elephant is restricted and you are not in the authorized list. Visit https://huggingface.co/AJRVIDEO/Elephant to ask for access. | [
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Capreolus/bert-base-msmarco | [
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"tf",
"jax",
"bert",
"text-classification",
"arxiv:2008.09093",
"transformers"
] | text-classification | {
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"no_rep... | 238 | null | ---
license: mit
---
### MattVidPro on Stable Diffusion
This is the `<mattvidpro>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualizer_inference.ipynb... | [
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0.... |
Capreolus/birch-bert-large-mb | [
"pytorch",
"tf",
"jax",
"bert",
"next-sentence-prediction",
"transformers"
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"no_rep... | 1 | null | Access to model AJRVIDEO/Elephantman is restricted and you are not in the authorized list. Visit https://huggingface.co/AJRVIDEO/Elephantman to ask for access. | [
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0.0300... |
Capreolus/birch-bert-large-msmarco_mb | [
"pytorch",
"tf",
"jax",
"bert",
"next-sentence-prediction",
"transformers"
] | null | {
"architectures": [
"BertForNextSentencePrediction"
],
"model_type": "bert",
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},
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"min_length": null,
"no_rep... | 1 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: test-trainer
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. -->
# te... | [
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Carlork314/Carlos | [] | null | {
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"num_beams... | 0 | 2022-10-03T23:32:40Z | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion-2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it,... | [
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Carlork314/Xd | [] | null | {
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"num_beams... | 0 | null | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: sourBlueBarneyTwo
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9800000190734863
---
# sourBlueBarneyTw... | [
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CarlosPR/mt5-spanish-memmories-analysis | [
"pytorch",
"mt5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
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],
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"no_repeat... | 7 | null | ---
library_name: stable-baselines3
tags:
- AntBulletEnv-v0
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: A2C
results:
- metrics:
- type: mean_reward
value: 1218.38 +/- 203.74
name: mean_reward
task:
type: reinforcement-learning
name:... | [
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Carolhuehuehuehue/Sla | [] | null | {
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"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetuning-review
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. -->
... | [
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Cat/Kitty | [] | null | {
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"num_beams... | 0 | null | # Grapheme-based statistical parametric synthesizer for Kinyarwanda
A Grapheme-based approach was chosen because they give acceptable performances for low-resource languages. For instance, this model was trained on approximately 5 hours of Kinyarwanda audios with their corresponding transcriptions, no further language... | [
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Cathy/reranking_model | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | {
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"RobertaForSequenceClassification"
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"... | 27 | null | ---
license: mit
---
### Filippo Palizzi Artworks on Stable Diffusion via Dreambooth
#### model by Capacap
This your the Stable Diffusion model fine-tuned the Filippo Palizzi Artworks concept taught to Stable Diffusion with Dreambooth.
It can be used by modifying the `instance_prompt`: **a painting by sks Filippo Paliz... | [
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dccuchile/albert-base-spanish-finetuned-ner | [
"pytorch",
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"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
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"no_re... | 14 | null | Access to model Mirimur/Wav2Vec2_Texas_ASR is restricted and you are not in the authorized list. Visit https://huggingface.co/Mirimur/Wav2Vec2_Texas_ASR to ask for access. | [
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dccuchile/albert-base-spanish-finetuned-pawsx | [
"pytorch",
"albert",
"text-classification",
"transformers"
] | text-classification | {
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"no... | 25 | null | Access to model LYTinn/finetuning-sentiment-model-3000-samples is restricted and you are not in the authorized list. Visit https://huggingface.co/LYTinn/finetuning-sentiment-model-3000-samples to ask for access. | [
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dccuchile/albert-base-spanish-finetuned-pos | [
"pytorch",
"albert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"AlbertForTokenClassification"
],
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},
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"no_re... | 5 | null | ---
datasets:
- bigscience/P3
language: en
license: apache-2.0
widget:
- text : "input: <extra_id_0> The item was packaged in bubble wrap. <extra_id_1>\n
- It was fragile.\n
- It was small.\n
output: It was fragile."
---
**Official repository**: [seonghyeonye/Flipped-Learning](https://github.com/seonghyeonye/Flipped-L... | [
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dccuchile/albert-large-spanish-finetuned-xnli | [
"pytorch",
"albert",
"text-classification",
"transformers"
] | text-classification | {
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"AlbertForSequenceClassification"
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"no... | 29 | null | ---
license: mit
---
### Chungus Poodl Pet on Stable Diffusion
This is the `<poodl-chungus-big>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualizer_i... | [
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... |
dccuchile/albert-tiny-spanish-finetuned-mldoc | [
"pytorch",
"albert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"AlbertForSequenceClassification"
],
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},
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"no... | 32 | null | ---
language:
- ms
tags:
- translation
metrics:
- sacrebleu
---
# finetune-translation-t5-super-tiny-standard-bahasa-cased
Finetuned T5 super tiny on EN-MS and MS-EN translation tasks.
## Dataset
1. EN-MS dataset, https://huggingface.co/datasets/mesolitica/en-ms
2. MS-EN dataset, https://huggingface.co/datasets/... | [
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dccuchile/albert-tiny-spanish-finetuned-ner | [
"pytorch",
"albert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
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"no_re... | 8 | null | ---
tags:
- generated_from_trainer
model-index:
- name: gpt2-gpt2-mc-weight0-epoch15
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. -->
# gpt2-gpt2-mc-weight0-epoch... | [
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dccuchile/albert-tiny-spanish-finetuned-pawsx | [
"pytorch",
"albert",
"text-classification",
"transformers"
] | text-classification | {
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],
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"no... | 29 | null | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: refinement-finetuned-mnli-kaggle-2
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. -->
# refinem... | [
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dccuchile/albert-tiny-spanish-finetuned-pos | [
"pytorch",
"albert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"AlbertForTokenClassification"
],
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},
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"min_length": null,
"no_re... | 5 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: distilbert-multilingual-uncased-oct-3
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... | [
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dccuchile/albert-tiny-spanish-finetuned-qa-mlqa | [
"pytorch",
"albert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"AlbertForQuestionAnswering"
],
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"max_length": null,
"min_length": null,
"no_repe... | 7 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec_korean
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. -->
# wav2vec_korean
This... | [
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dccuchile/albert-tiny-spanish-finetuned-xnli | [
"pytorch",
"albert",
"text-classification",
"transformers"
] | text-classification | {
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"no... | 31 | null | ---
tags:
- generated_from_trainer
model-index:
- name: bert-base-uncased-bert-base-uncased-mc-weight0-epoch15
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. -->
# ... | [
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dccuchile/albert-xlarge-spanish-finetuned-qa-mlqa | [
"pytorch",
"albert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"AlbertForQuestionAnswering"
],
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"min_length": null,
"no_repe... | 7 | 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
config: PAN-X.de
split: train
... | [
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dccuchile/albert-xxlarge-spanish-finetuned-mldoc | [
"pytorch",
"albert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
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],
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"min_length": null,
"no... | 26 | null | ---
license: mit
---
### Liminal spaces 2.0 on Stable Diffusion
This is the `liminal image` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualizer_infere... | [
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dccuchile/albert-xxlarge-spanish-finetuned-pawsx | [
"pytorch",
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"transformers"
] | text-classification | {
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"no... | 26 | null | ---
library_name: stable-baselines3
tags:
- LunarLander-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: PPO
results:
- metrics:
- type: mean_reward
value: 240.84 +/- 20.71
name: mean_reward
task:
type: reinforcement-learning
name: re... | [
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dccuchile/albert-xxlarge-spanish-finetuned-xnli | [
"pytorch",
"albert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
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"min_length": null,
"no... | 68 | null | ---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: banglabert-bert-finetuned-ner
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 ... | [
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dccuchile/albert-base-spanish | [
"pytorch",
"tf",
"albert",
"pretraining",
"es",
"dataset:large_spanish_corpus",
"transformers",
"spanish",
"OpenCENIA"
] | null | {
"architectures": [
"AlbertForPreTraining"
],
"model_type": "albert",
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngr... | 586 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
model-index:
- name: vit-base-patch16-224-finetuned-flower
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 r... | [
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0.02... |
dccuchile/albert-large-spanish | [
"pytorch",
"tf",
"albert",
"pretraining",
"es",
"dataset:large_spanish_corpus",
"transformers",
"spanish",
"OpenCENIA"
] | null | {
"architectures": [
"AlbertForPreTraining"
],
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"no_repeat_ngr... | 75 | null | ---
tags:
- conversational
---
# Kashiwagi Osamu DialoGPT Model | [
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dccuchile/albert-tiny-spanish | [
"pytorch",
"tf",
"albert",
"pretraining",
"es",
"dataset:large_spanish_corpus",
"transformers",
"spanish",
"OpenCENIA"
] | null | {
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],
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"min_length": null,
"no_repeat_ngr... | 393 | null | ---
library_name: stable-baselines3
tags:
- LunarLander-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: PPO
results:
- metrics:
- type: mean_reward
value: 249.94 +/- 23.25
name: mean_reward
task:
type: reinforcement-learning
name: re... | [
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dccuchile/albert-xxlarge-spanish | [
"pytorch",
"tf",
"albert",
"pretraining",
"es",
"dataset:large_spanish_corpus",
"transformers",
"spanish",
"OpenCENIA"
] | null | {
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],
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"no_repeat_ngr... | 42 | null | ---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: ijelid-indobertweet
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 comme... | [
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dccuchile/bert-base-spanish-wwm-cased-finetuned-pawsx | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
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"no_rep... | 25 | null | ---
license: apache-2.0
tags:
- translation
- generated_from_trainer
metrics:
- bleu
model-index:
- name: marian-finetuned-kde4-en-to-ja_kftt
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, th... | [
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0.05... |
dccuchile/bert-base-spanish-wwm-cased-finetuned-pos | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
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},
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"max_length": null,
"min_length": null,
"no_repeat... | 1 | null | ---
language:
- en
tags:
- text-classification
- claim-detection
license: "mit"
datasets:
- Nithiwat/claim-detection
widget:
- text: "This is the best cast iron skillet you will ever buy."
- text: "Barack Obama nominated Hilary Clinton as his secretary of state on Monday."
- text: "On a shelf, there are five books:... | [
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0.016... |
dccuchile/bert-base-spanish-wwm-uncased-finetuned-pawsx | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
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"no_rep... | 24 | null | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: gpt2-poetry-model
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. -->
# gpt2-poetry-model
This ... | [
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dccuchile/distilbert-base-spanish-uncased-finetuned-pawsx | [
"pytorch",
"distilbert",
"text-classification",
"transformers"
] | text-classification | {
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... | 29 | null | ---
license: apache-2.0
tags:
- translation
- generated_from_trainer
metrics:
- bleu
model-index:
- name: marian-finetuned-kftt_kde4-en-to-ja
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, th... | [
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dccuchile/distilbert-base-spanish-uncased-finetuned-pos | [
"pytorch",
"distilbert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"DistilBertForTokenClassification"
],
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... | 3 | null | ---
language:
- en
tags:
- text-classification
- claim-detection
license: "mit"
datasets:
- Nithiwat/claim-detection
widget:
- text: "This is the best cast iron skillet you will ever buy."
- text: "Barack Obama nominated Hilary Clinton as his secretary of state on Monday."
- text: "On a shelf, there are five books:... | [
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dccuchile/distilbert-base-spanish-uncased | [
"pytorch",
"distilbert",
"fill-mask",
"es",
"dataset:large_spanish_corpus",
"transformers",
"spanish",
"OpenCENIA",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"DistilBertForMaskedLM"
],
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},
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"min_length": null,
"no_repea... | 670 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
- f1
model-index:
- name: finetuning-sentiment-model-3000-samples
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
config: plain_text
... | [
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CennetOguz/distilbert-base-uncased-finetuned-recipe-1 | [
"pytorch",
"tensorboard",
"distilbert",
"fill-mask",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
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"no_repea... | 7 | null | ---
tags:
- stanza
- token-classification
library_name: stanza
language: bn
license: apache-2.0
---
# Stanza model for Bengali (bn)
Stanza is a collection of accurate and efficient tools for the linguistic analysis of many human languages. Starting from raw text to syntactic analysis and entity recognition, Stanza brin... | [
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CennetOguz/distilbert-base-uncased-finetuned-recipe-accelerate-1 | [
"pytorch",
"distilbert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"DistilBertForMaskedLM"
],
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},
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"min_length": null,
"no_repea... | 1 | null | ---
tags:
- stanza
- token-classification
library_name: stanza
language: ml
license: apache-2.0
---
# Stanza model for Malayalam (ml)
Stanza is a collection of accurate and efficient tools for the linguistic analysis of many human languages. Starting from raw text to syntactic analysis and entity recognition, Stanza br... | [
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0.... |
CennetOguz/distilbert-base-uncased-finetuned-recipe-accelerate | [
"pytorch",
"distilbert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"DistilBertForMaskedLM"
],
"model_type": "distilbert",
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},
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"min_length": null,
"no_repea... | 7 | null | ---
tags:
- stanza
- token-classification
library_name: stanza
language: sd
license: apache-2.0
---
# Stanza model for Sindhi (sd)
Stanza is a collection of accurate and efficient tools for the linguistic analysis of many human languages. Starting from raw text to syntactic analysis and entity recognition, Stanza bring... | [
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0... |
CennetOguz/distilbert-base-uncased-finetuned-recipe | [
"pytorch",
"tensorboard",
"distilbert",
"fill-mask",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"DistilBertForMaskedLM"
],
"model_type": "distilbert",
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},
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"max_length": null,
"min_length": null,
"no_repea... | 2 | null | ---
tags:
- stanza
- token-classification
library_name: stanza
language: si
license: apache-2.0
---
# Stanza model for Sinhala (si)
Stanza is a collection of accurate and efficient tools for the linguistic analysis of many human languages. Starting from raw text to syntactic analysis and entity recognition, Stanza brin... | [
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0.0... |
Chaddmckay/Cdm | [] | null | {
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"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: mit
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: mBART_slang_to_standard_4
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. -->
# ... | [
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0.034... |
Chaewon/mnmt_decoder_en_gpt2 | [] | null | {
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"num_beams... | 0 | null | ---
language:
- en
tags:
- stable-diffusion
- text-to-image
license: bigscience-bloom-rail-1.0
inference: true
---
# stable-diffusion-wikiart | [
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0.0... |
Chaima/TunBerto | [] | null | {
"architectures": null,
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"num_beams... | 0 | null | ---
language:
- en
tags:
- stable-diffusion
- text-to-image
license: bigscience-bloom-rail-1.0
inference: true
---
# stable-diffusion-wikiart
sd-wikiart-v2 is a stable diffusion model that has been fine-tuned on the [wikiart dataset](https://huggingface.co/datasets/fusing/wikiart_captions) to generate artistic image... | [
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0.... |
chainyo/speaker-recognition-meetup | [] | null | {
"architectures": null,
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"num_beams... | 1 | null | ---
license: mit
---
### crb-surrealz on Stable Diffusion
This is the `<crbsurreal>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualizer_inference.ipy... | [
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0.013456758111715317,
0.03... |
ChaitanyaU/FineTuneLM | [] | null | {
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"num_beams... | 0 | 2022-10-04T09:02:01Z | ---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
datasets:
- xfun
model-index:
- name: layoutxlm-finetuned-xfund-fr
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 ... | [
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0.0... |
Chakita/KNUBert | [
"pytorch",
"tensorboard",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
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},
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"min_length": null,
"no_repeat_ngra... | 20 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: dataset_radiology_20220912.tsv
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. -->
# data... | [
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Chakita/Kalbert | [
"pytorch",
"tensorboard",
"albert",
"fill-mask",
"transformers",
"generated_from_trainer",
"license:mit",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"AlbertForMaskedLM"
],
"model_type": "albert",
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},
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"no_repeat_ngram_... | 5 | 2022-10-04T09:22:12Z |
---
language: en
---
<p align="center">
<img src="https://doctr-static.mindee.com/models?id=v0.3.1/Logo_doctr.gif&src=0" width="60%">
</p>
**Optical Character Recognition made seamless & accessible to anyone, powered by TensorFlow 2 & PyTorch**
## Task: recognition
https://github.com/mindee/doctr
### Example usag... | [
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-0.014105213806033134... |
Chakita/KannadaBERT | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"masked-lm",
"fill-in-the-blanks",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
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},
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 5 | 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:... | [
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... |
Chakita/gpt2_mwp | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
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},
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"no_repeat_ngram_size... | 6 | null | Access to model maxchoi/aitest is restricted and you are not in the authorized list. Visit https://huggingface.co/maxchoi/aitest to ask for access. | [
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0.03413255140185356,
0.017956644296646118,
0.02618301473557949,
0.0363... |
Chalponkey/DialoGPT-small-Barry | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
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"min_length": null,
"no_repeat_ngram_size... | 11 | 2022-10-04T09:36:21Z | ---
tags:
- generated_from_trainer
model-index:
- name: bert-base-uncased-bert-base-uncased-mc-weight0.25-epoch15
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. -->
... | [
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0.004876531660556793,
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0.04575... |
Champion/test_upload_vox2_wavlm_epoch8 | [
"sidekit",
"audio"
] | null | {
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"num_beams... | 0 | null | ---
tags:
- autotrain
- vision
- image-classification
datasets:
- mouss/autotrain-data-damages
widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg
example_title: Tiger
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg
example_title: Teapot
- s... | [
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0.005584943573921919,
0.0023393260780721903,
... |
Cheapestmedsshop/Buymodafinilus | [] | null | {
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"num_beams... | 0 | null | ---
license: cc-by-nc-4.0
pipeline_tag: fill-mask
tags:
- legal
language:
- da
datasets:
- multi_eurlex
- DDSC/partial-danish-gigaword-no-twitter
model-index:
- name: coastalcph/danish-legal-bert-base
results: []
---
# Danish LegalBERT (derivative of Maltehb/danish-bert-botxo)
This model is a derivative of [Maltehb... | [
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0.... |
Cheatham/xlm-roberta-base-finetuned | [
"pytorch",
"xlm-roberta",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"XLMRobertaForSequenceClassification"
],
"model_type": "xlm-roberta",
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},
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... | 20 | null |
---
license: cc-by-4.0
metrics:
- bleu4
- meteor
- rouge-l
- bertscore
- moverscore
language: en
datasets:
- lmqg/qg_squad
pipeline_tag: text2text-generation
tags:
- question generation
- answer extraction
widget:
- text: "generate question: <hl> Beyonce <hl> further expanded her acting career, starring as blues singe... | [
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0.009750031866133213,
0.02... |
Cheatham/xlm-roberta-large-finetuned-d1 | [
"pytorch",
"xlm-roberta",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"XLMRobertaForSequenceClassification"
],
"model_type": "xlm-roberta",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
... | 20 | 2022-10-04T10:12:59Z | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
- f1
model-index:
- name: finetuning-sentiment-model-3000-samples-imdb
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
config: plain_text
... | [
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Cheatham/xlm-roberta-large-finetuned-d1r01 | [
"pytorch",
"xlm-roberta",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"XLMRobertaForSequenceClassification"
],
"model_type": "xlm-roberta",
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... | 21 | 2022-10-04T10:47:00Z | ---
tags:
- generated_from_trainer
datasets:
- tweet_eval
metrics:
- accuracy
- f1
model-index:
- name: finetuning-cardiffnlp-twitter-roberta-base-sentiment
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: tweet_eval
type: tweet_eval
config: senti... | [
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Cheatham/xlm-roberta-large-finetuned-r01 | [
"pytorch",
"xlm-roberta",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"XLMRobertaForSequenceClassification"
],
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... | 23 | null | ---
license: bigscience-bloom-rail-1.0
language:
- en
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
---
このモデルは、アイドルマスター シャイニーカラーズに登場するアイドル、芹沢あさひのイラストを生成するのに特化したStable-DiffusionのDiffuser用のモデルです。
This model is for Diffuser, a Stable-Diffusion specialized for generating illustrations of Asahi Se... | [
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0.0... |
ChukSamuels/DialoGPT-small-Dr.FauciBot | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
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"min_length": null,
"no_repeat_ngram_size... | 13 | null | ---
tags:
- autotrain
- token-classification
language:
- en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- Akshata/autotrain-data-person-name-validity1
co2_eq_emissions:
emissions: 0.015012024821802214
---
# Model Trained Using AutoTrain
- Problem type: Entity Extraction
- Model ID: 1655358687
- CO2 Emissions (i... | [
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Chun/DialoGPT-small-dailydialog | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 10 | null | ---
language:
- en
tags:
- esc
datasets:
- earnings22
---
To reproduce this run, first call `get_ctc_tokenizer.py` to train the CTC tokenizer and then execute the following command to train the CTC system:
```python
#!/usr/bin/env bash
python run_flax_speech_recognition_ctc.py \
--model_name_or_path="esc-ben... | [
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... |
Cilan/dalle-knockoff | [] | null | {
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
language:
- en
tags:
- esc
datasets:
- voxpopuli
---
To reproduce this run, execute:
```python
#!/usr/bin/env bash
python run_flax_speech_recognition_seq2seq.py \
--dataset_name="esc-benchmark/esc-datasets" \
--model_name_or_path="esc-benchmark/wav2vec2-aed-pretrained" \
--dataset_config_n... | [
-0.025953218340873718,
-0.02337774634361267,
-0.002673591021448374,
0.047640491276979446,
0.047614432871341705,
0.019760774448513985,
-0.007995267398655415,
-0.011722669005393982,
-0.039550527930259705,
0.05689780041575432,
0.027488548308610916,
-0.008609963580965996,
0.0078864311799407,
0... |
Cinnamon/electra-small-japanese-generator | [
"pytorch",
"electra",
"fill-mask",
"ja",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"ElectraForMaskedLM"
],
"model_type": "electra",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 19 | null | ---
language:
- en
tags:
- esc
datasets:
- spgispeech
---
To reproduce this run, execute:
```python
#!/usr/bin/env bash
python run_flax_speech_recognition_seq2seq.py \
--dataset_name="esc-benchmark/esc-datasets" \
--model_name_or_path="esc-benchmark/wav2vec2-aed-pretrained" \
--dataset_config_... | [
-0.022427525371313095,
-0.020836753770709038,
-0.012175852432847023,
0.04353441298007965,
0.0513603650033474,
0.017291104421019554,
-0.006148435175418854,
-0.01091462466865778,
-0.045359861105680466,
0.05924549326300621,
0.02464623749256134,
-0.000385155959520489,
-0.0004152447800152004,
0... |
ClydeWasTaken/DialoGPT-small-joshua | [
"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 | ---
language:
- en
tags:
- esc
datasets:
- spgispeech
---
To reproduce this run, execute:
```python
#!/usr/bin/env bash
CUDA_VISIBLE_DEVICES=0 python run_speech_recognition_whisper.py \
--model_name_or_path="medium.en" \
--dataset_name="esc-benchmark/esc-datasets" \
--dataset_config_name="spgispeech" \
--max_st... | [
-0.030391579493880272,
-0.012620359659194946,
-0.015520880930125713,
0.059337567538022995,
0.06528855860233307,
0.01877775229513645,
-0.006045748479664326,
-0.0014874179614707828,
-0.057603511959314346,
0.07059233635663986,
0.024778464809060097,
-0.005111389327794313,
-0.008748754858970642,
... |
CoShin/XLM-roberta-large_ko_en_nil_sts | [] | 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 | ---
license: apache-2.0
tags:
- vision
- image-classification
datasets:
- imagenet-1k
--- | [
-0.015443696640431881,
-0.02117861807346344,
0.0028278580866754055,
0.006564872805029154,
0.051361147314310074,
-0.029106883332133293,
-0.010926221497356892,
0.02620372734963894,
-0.016204209998250008,
0.03808508440852165,
0.01571081206202507,
0.016049688681960106,
0.014702762477099895,
0.... |
CoachCarter/distilbert-base-uncased-finetuned-squad | [] | 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 | ---
language:
- en
tags:
- esc
datasets:
- earnings22
---
To reproduce this run, execute:
```python
#!/usr/bin/env bash
CUDA_VISIBLE_DEVICES=0 python run_speech_recognition_whisper.py \
--model_name_or_path="medium.en" \
--dataset_name="esc-benchmark/esc-datasets" \
--dataset_config_name="earnings22" \
--max_st... | [
-0.03315960243344307,
-0.005936505738645792,
-0.0011198701104149222,
0.05126576125621796,
0.06569559872150421,
0.01687726005911827,
-0.005690066143870354,
-0.0027059137355536222,
-0.05246536433696747,
0.06845657527446747,
0.029584873467683792,
-0.007077221758663654,
-0.0048498776741325855,
... |
CodeDanCode/SP-KyleBot | [
"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... | 15 | null | ---
language:
- en
tags:
- esc
datasets:
- ami
---
To reproduce this run, execute:
```python
#!/usr/bin/env bash
CUDA_VISIBLE_DEVICES=0 python run_speech_recognition_whisper.py \
--model_name_or_path="medium.en" \
--dataset_name="esc-benchmark/esc-datasets" \
--dataset_config_name="ami" \
--max_steps="2500" \
... | [
-0.03570976108312607,
-0.014115097932517529,
-0.006622917018830776,
0.06376107037067413,
0.06150558963418007,
0.01756763644516468,
-0.004718995187431574,
-0.00520725455135107,
-0.05008983984589577,
0.06502939015626907,
0.02798672579228878,
0.0010105007095262408,
-0.006442016921937466,
0.03... |
CodeNinja1126/bert-p-encoder | [
"pytorch"
] | 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... | 3 | null | ---
language:
- en
tags:
- esc
datasets:
- switchboard
---
To reproduce this run, execute:
```python
#!/usr/bin/env bash
CUDA_VISIBLE_DEVICES=0 python run_speech_recognition_whisper.py \
--model_name_or_path="medium.en" \
--dataset_name="esc-benchmark/esc-datasets" \
--dataset_config_name="switchboard" \
--max_... | [
-0.05392079055309296,
-0.004744679667055607,
-0.01554530207067728,
0.06929761171340942,
0.05878686159849167,
0.014485792256891727,
-0.0032668637577444315,
-0.0017238581785932183,
-0.05564173683524132,
0.06930939853191376,
0.018068749457597733,
-0.00632406584918499,
-0.0067598577588796616,
... |
CodeNinja1126/test-model | [
"pytorch",
"jax",
"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... | 24 | null | ---
language:
- en
tags:
- esc
datasets:
- chime4
---
To reproduce this run, execute:
```python
#!/usr/bin/env bash
CUDA_VISIBLE_DEVICES=0 python run_speech_recognition_whisper.py \
--model_name_or_path="medium.en" \
--dataset_name="esc-benchmark/esc-datasets" \
--dataset_config_name="chime4" \
--max_steps="250... | [
-0.03943931311368942,
-0.010555429384112358,
-0.005303099751472473,
0.057676155120134354,
0.06384152173995972,
0.015799466520547867,
-0.0108809107914567,
-0.0061872354708611965,
-0.05008973181247711,
0.0722339078783989,
0.023801133036613464,
-0.005161769222468138,
0.0008240202441811562,
0.... |
CoderEFE/DialoGPT-marxbot | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational",
"has_space"
] | 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... | 11 | 2022-10-04T14:29:35Z | ---
language:
- en
tags:
- esc
datasets:
- librispeech
---
To reproduce this run, execute:
```python
#!/usr/bin/env bash
CUDA_VISIBLE_DEVICES=0 python run_speech_recognition_rnnt.py \
--config_path="conf/conformer_transducer_bpe_xlarge.yaml" \
--model_name_or_path="stt_en_conformer_transducer_xlarge" ... | [
-0.038730133324861526,
-0.005902512464672327,
-0.010362038388848305,
0.04577885568141937,
0.06716432422399521,
0.02135086990892887,
-0.014115765690803528,
-0.026728279888629913,
-0.05248405784368515,
0.06356705725193024,
0.01168674323707819,
0.004083874169737101,
-0.002421298297122121,
0.0... |
CoderEFE/DialoGPT-medium-marx | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"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... | 7 | null | ---
language:
- en
tags:
- esc
datasets:
- common_voice
---
To reproduce this run, execute:
```python
#!/usr/bin/env bash
CUDA_VISIBLE_DEVICES=0 python run_speech_recognition_rnnt.py \
--config_path="conf/conformer_transducer_bpe_xlarge.yaml" \
--model_name_or_path="stt_en_conformer_transducer_xlarge"... | [
-0.042189378291368484,
-0.006724124774336815,
-0.01285801362246275,
0.045513588935136795,
0.07316292822360992,
0.02432515099644661,
-0.008077237755060196,
-0.02462007850408554,
-0.046121641993522644,
0.05699412152171135,
0.014212542213499546,
0.0016483928775414824,
0.0014650498051196337,
0... |
CoffeeAddict93/gpt1-call-of-the-wild | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 8 | null | ---
language:
- en
tags:
- esc
datasets:
- tedlium
---
To reproduce this run, execute:
```python
#!/usr/bin/env bash
CUDA_VISIBLE_DEVICES=0 python run_speech_recognition_rnnt.py \
--config_path="conf/conformer_transducer_bpe_xlarge.yaml" \
--model_name_or_path="stt_en_conformer_transducer_xlarge" \
... | [
-0.039033886045217514,
-0.005972825922071934,
-0.008165470324456692,
0.04727892577648163,
0.06717097759246826,
0.03004346787929535,
-0.011147293262183666,
-0.029012368991971016,
-0.0489356555044651,
0.056313157081604004,
0.005043921992182732,
-0.005723100155591965,
0.00314147537574172,
0.0... |
CoffeeAddict93/gpt1-modest-proposal | [
"pytorch",
"openai-gpt",
"text-generation",
"transformers",
"has_space"
] | text-generation | {
"architectures": [
"OpenAIGPTLMHeadModel"
],
"model_type": "openai-gpt",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 11 | 2022-10-04T14:36:03Z | ---
language:
- en
tags:
- esc
datasets:
- voxpopuli
---
To reproduce this run, execute:
```python
#!/usr/bin/env bash
CUDA_VISIBLE_DEVICES=0 python run_speech_recognition_rnnt.py \
--config_path="conf/conformer_transducer_bpe_xlarge.yaml" \
--model_name_or_path="stt_en_conformer_transducer_xlarge" \
... | [
-0.040450867265462875,
-0.007456466555595398,
-0.003058101050555706,
0.04692698270082474,
0.06437289714813232,
0.02454538270831108,
-0.01036021951586008,
-0.025315428152680397,
-0.04573652148246765,
0.06168733164668083,
0.015924515202641487,
0.00044587432057596743,
0.0036353725008666515,
0... |
CoffeeAddict93/gpt2-call-of-the-wild | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"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
tags:
- esc
datasets:
- gigaspeech
---
To reproduce this run, execute:
```python
#!/usr/bin/env bash
CUDA_VISIBLE_DEVICES=0 python run_speech_recognition_rnnt.py \
--config_path="conf/conformer_transducer_bpe_xlarge.yaml" \
--model_name_or_path="stt_en_conformer_transducer_xlarge" \... | [
-0.04021499678492546,
-0.004862045869231224,
-0.009926109574735165,
0.04447825998067856,
0.06930497288703918,
0.023093856871128082,
-0.010377377271652222,
-0.028519434854388237,
-0.05004572495818138,
0.06243811175227165,
0.011307358741760254,
0.007380266673862934,
-0.0013402275508269668,
0... |
CoffeeAddict93/gpt2-medium-call-of-the-wild | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 14 | null | ---
language:
- en
tags:
- esc
datasets:
- spgispeech
---
To reproduce this run, execute:
```python
#!/usr/bin/env bash
CUDA_VISIBLE_DEVICES=0 python run_speech_recognition_rnnt.py \
--config_path="conf/conformer_transducer_bpe_xlarge.yaml" \
--model_name_or_path="stt_en_conformer_transducer_xlarge" \... | [
-0.03872286155819893,
-0.007172151934355497,
-0.012097889557480812,
0.04565008357167244,
0.0699407309293747,
0.022637218236923218,
-0.01073142234236002,
-0.022980429232120514,
-0.054481226950883865,
0.06319630891084671,
0.009788772091269493,
0.005739352200180292,
-0.003013974754139781,
0.0... |
CoffeeAddict93/gpt2-medium-modest-proposal | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 7 | null | ---
language:
- en
tags:
- esc
datasets:
- earnings22
---
To reproduce this run, execute:
```python
#!/usr/bin/env bash
CUDA_VISIBLE_DEVICES=0 python run_speech_recognition_rnnt.py \
--config_path="conf/conformer_transducer_bpe_xlarge.yaml" \
--model_name_or_path="stt_en_conformer_transducer_xlarge" \... | [
-0.03973369300365448,
-0.003944457042962313,
-0.0024426935706287622,
0.0414109006524086,
0.07089059054851532,
0.022526124492287636,
-0.012311375699937344,
-0.024534504860639572,
-0.051671747118234634,
0.06317481398582458,
0.013615782372653484,
0.0017756959423422813,
-0.0012687011621892452,
... |
CoffeeAddict93/gpt2-modest-proposal | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 12 | null | ---
language:
- en
tags:
- esc
datasets:
- ami
---
To reproduce this run, execute:
```python
#!/usr/bin/env bash
CUDA_VISIBLE_DEVICES=0 python run_speech_recognition_rnnt.py \
--config_path="conf/conformer_transducer_bpe_xlarge.yaml" \
--model_name_or_path="stt_en_conformer_transducer_xlarge" \
... | [
-0.04159362614154816,
-0.010366235859692097,
-0.0064444453455507755,
0.049976129084825516,
0.06676917523145676,
0.022907646372914314,
-0.01032252423465252,
-0.02545098215341568,
-0.04842725023627281,
0.06007201597094536,
0.013073171488940716,
0.009166480973362923,
-0.0010190473403781652,
0... |
CogComp/bart-faithful-summary-detector | [
"pytorch",
"jax",
"bart",
"text-classification",
"en",
"dataset:xsum",
"transformers",
"xsum",
"license:cc-by-sa-4.0"
] | text-classification | {
"architectures": [
"BartForSequenceClassification"
],
"model_type": "bart",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": 1,
"max_length": 128,
"min_length": 12,
"no_repeat_ng... | 234 | null | ---
license: mit
---
### jfj on Stable Diffusion via Dreambooth
#### model by Seonauta
This your the Stable Diffusion model fine-tuned the jfj concept taught to Stable Diffusion with Dreambooth.
It can be used by modifying the `instance_prompt`: **a photo of sks jfj**
You can also train your own concepts and upload th... | [
-0.043001461774110794,
-0.02531900443136692,
-0.017018478363752365,
0.02090868167579174,
0.01684213988482952,
0.01208560448139906,
0.0018364136340096593,
0.0006215665489435196,
-0.033243175595998764,
0.033719759434461594,
0.009990300051867962,
0.0004442991048563272,
0.0029141330160200596,
... |
CogComp/roberta-temporal-predictor | [
"pytorch",
"roberta",
"fill-mask",
"arxiv:2202.00436",
"transformers",
"license:mit",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"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_ngra... | 14 | null | ---
language:
- en
tags:
- esc
datasets:
- switchboard
---
To reproduce this run, execute:
```python
#!/usr/bin/env bash
CUDA_VISIBLE_DEVICES=0 python run_speech_recognition_rnnt.py \
--config_path="conf/conformer_transducer_bpe_xlarge.yaml" \
--model_name_or_path="stt_en_conformer_transducer_xlarge" ... | [
-0.05893956124782562,
-0.0021684584207832813,
-0.012208539061248302,
0.05532458424568176,
0.06475342065095901,
0.020748985931277275,
-0.008091901428997517,
-0.021117588505148888,
-0.05341522395610809,
0.06398340314626694,
0.006050208117812872,
0.0036753921303898096,
-0.0017808572156354785,
... |
CohleM/bert-nepali-tokenizer | [] | 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 | ---
language:
- en
tags:
- esc
datasets:
- chime4
---
To reproduce this run, execute:
```python
#!/usr/bin/env bash
CUDA_VISIBLE_DEVICES=0 python run_speech_recognition_rnnt.py \
--config_path="conf/conformer_transducer_bpe_xlarge.yaml" \
--model_name_or_path="stt_en_conformer_transducer_xlarge" \
... | [
-0.0441080741584301,
-0.007407570257782936,
-0.003490859642624855,
0.046682510524988174,
0.06803778558969498,
0.0210404172539711,
-0.014805789105594158,
-0.024424973875284195,
-0.04763783887028694,
0.06665254384279251,
0.010887267999351025,
0.004521091002970934,
0.005856853909790516,
0.041... |
CohleM/mbert-nepali-tokenizer | [] | 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 | ---
license: apache-2.0
tags:
- question-answering
- generated_from_trainer
model-index:
- name: roberta-base-squad2-nq-bioasq
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 ... | [
-0.02457895129919052,
-0.01688508689403534,
-0.014364244416356087,
0.028438441455364227,
0.017833389341831207,
0.03142538666725159,
-0.006603002082556486,
-0.006655260920524597,
-0.04045587405562401,
0.005517121870070696,
0.029783159494400024,
0.00001883568984339945,
-0.00038344398490153253,... |
ComCom/gpt2-large | [
"pytorch",
"gpt2",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"GPT2Model"
],
"model_type": "gpt2",
"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 | 2022-10-04T15:00:53Z | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: south-indian-foods
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.6666666865348816
---
# south-indian-fo... | [
-0.0059613571502268314,
0.0028135611210018396,
0.020267486572265625,
0.03827664256095886,
0.032514821738004684,
-0.0222864281386137,
-0.0160463135689497,
0.011519843712449074,
-0.005021103657782078,
0.05212050676345825,
0.029505282640457153,
-0.011113431304693222,
0.010580585338175297,
0.0... |
Connor/DialoGPT-small-rick | [
"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... | 7 | null | ---
tags:
- generated_from_trainer
model-index:
- name: EleutherAI_gpt-neo-125M-stablediffionprompts
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. -->
# EleutherAI... | [
-0.04349290207028389,
0.005481769796460867,
-0.030213890597224236,
0.02846500277519226,
0.0459807813167572,
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0.008375110104680061,
-0.0191400907933712,
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0.04772372916340828,
0.022743115201592445,
-0.008947715163230896,
-0.005617254879325628,
0.0460... |
Connorvr/BrightBot-small | [
"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... | 7 | 2022-10-04T15:26:51Z | ---
language: en
inference: false
tags:
- text-generation
license: other
commercial: false
model-index:
- name: inverse-scaling/opt-350m_eval
results:
- task:
type: zero-shot-classification
name: Zero-Shot Text Classification
dataset:
name: inverse-scaling/NeQA
type: inverse-scaling/NeQA... | [
0.0071775345131754875,
-0.025924520567059517,
-0.028801141306757927,
0.03291187062859535,
0.05827243998646736,
0.019754840061068535,
-0.027611099183559418,
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-0.0446050688624382,
0.06222647428512573,
0.013509039767086506,
-0.014381497167050838,
0.013234916143119335,
0.0... |
Connorvr/TeachingGen | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"generated_from_trainer",
"license:mit"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"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 | 2022-10-04T15:28:41Z | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: amazon-review-sentiment-analysis
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. -->
# am... | [
-0.03698492795228958,
0.004661934915930033,
-0.01592067815363407,
0.04190695658326149,
0.029025590047240257,
0.027411354705691338,
-0.009566698223352432,
0.0002795895852614194,
-0.06457004696130753,
0.05935470014810562,
0.05680200085043907,
-0.020967334508895874,
0.00719326501712203,
0.036... |
ConstellationBoi/Oop | [] | 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 | 2022-10-04T15:31:13Z | ---
language: en
thumbnail: http://www.huggingtweets.com/breedlove22/1664897591383/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; wid... | [
0.0035271523520350456,
-0.036036789417266846,
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0.058309245854616165,
0.05156978219747543,
0.010878123342990875,
-0.02194327861070633,
-0.012772975489497185,
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0.03858697786927223,
0.0038229702040553093,
0.0027130821254104376,
-0.013780108653008938,
... |
Contrastive-Tension/BERT-Base-CT-STSb | [
"pytorch",
"tf",
"jax",
"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... | 5 | 2022-10-04T15:31:40Z | ---
language: hu
license: apache-2.0
datasets:
- wikipedia
tags:
- generated_from_keras_callback
- hubert
model-index:
- name: hubert-tiny-wiki
results: []
---
# hubert-tiny-wiki
This model was trained from scratch on the Wikipedia subset of Hungarian Webcorpus 2.0 with MLM and SOP tasks.
### Pre-Training Paramete... | [
-0.0032842729706317186,
-0.028759920969605446,
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0.03922107443213463,
0.006402978207916021,
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0.058311183005571365,
0.008453126065433025,
-0.0004649233596865088,
0.008284137584269047,
... |
Contrastive-Tension/BERT-Base-CT | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"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... | 16 | 2022-10-04T15:32:15Z | ---
language: en
license: other
tags:
- text-generation
- opt
inference: false
commercial: false
model-index:
- name: inverse-scaling/opt-125m_eval
results:
- task:
type: zero-shot-classification
name: Zero-Shot Text Classification
dataset:
name: inverse-scaling/NeQA
type: inverse-scalin... | [
-0.017381398007273674,
-0.017983922734856606,
-0.004915930330753326,
0.02754029631614685,
0.06363201141357422,
0.014894344843924046,
-0.023653406649827957,
-0.015043003484606743,
-0.038269344717264175,
0.04768432304263115,
0.012845320627093315,
-0.015522023662924767,
0.016280069947242737,
... |
Contrastive-Tension/BERT-Base-NLI-CT | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"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... | 9 | 2022-10-04T15:33:25Z | ---
language: hu
license: apache-2.0
datasets:
- wikipedia
tags:
- generated_from_keras_callback
- hubert
model-index:
- name: hubert-small-wiki-seq128
results: []
---
# hubert-small-wiki-seq128
Fully trained model with the second phase of training is available here: [SzegedAI/hubert-small-wiki](https://huggingface... | [
-0.001980505883693695,
-0.02928963117301464,
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0.05770711600780487,
0.007480612490326166,
0.00234058010391891,
0.010893065482378006,
0.041... |
Contrastive-Tension/BERT-Base-Swe-CT-STSb | [
"pytorch",
"tf",
"jax",
"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... | 126 | 2022-10-04T15:34:52Z | ---
language: en
license: other
tags:
- text-generation
- opt
inference: false
commercial: false
model-index:
- name: inverse-scaling/opt-1.3b_eval
results:
- task:
type: zero-shot-classification
name: Zero-Shot Text Classification
dataset:
name: inverse-scaling/NeQA
type: inverse-scalin... | [
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0.04909076541662216,
0.010612579993903637,
-0.01430417038500309,
0.01874380186200142,
0.053... |
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