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 |
|---|---|---|---|---|---|---|---|
BumBelDumBel/TRUMP | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers",
"generated_from_trainer",
"license:mit"
] | text-generation | {
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"GPT2LMHeadModel"
],
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"no_repeat_ngram_size... | 5 | null | ---
language:
- multilingual
tags:
- STILT
- retraining
- multi-task learning
datasets:
- SemEval 2022
---
## Sem-RemmmBERT
This is the SemEval MaChAmp Multitask Multilingual BERT model. This model is retrained from remBERT (https://huggingface.co/google/rembertased).
The retraining is done based on all SemEval ... | [
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BumBelDumBel/ZORK_AI_FANTASY | [] | null | {
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"num_beams... | 0 | null | ---
language: cs
license: cc-by-nc-sa-4.0
datasets:
- csTenTen17
---
# CzeGPT-2
CzeGPT-2 is a Czech version of GPT-2 language model by OpenAI with LM Head on top. The model has the same architectural dimensions as the GPT-2 small (12 layers, 12 heads, 1024 tokens on input/output, and embedding vectors with 768 dimens... | [
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Buntan/BuntanAI | [] | null | {
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"num_beams... | 0 | null | ---
language: cs
license: cc-by-nc-sa-4.0
datasets:
- csTenTen17
---
# CzeGPT-2_summarizer
CzeGPT-2 summarizer is a Czech summarizer built upon the <a href="https://huggingface.co/MU-NLPC/CzeGPT-2">CzeGPT-2</a> model. The model has the same architectural dimensions as the GPT-2 small (12 layers, 12 heads, 1024 tokens... | [
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CAMeL-Lab/bert-base-arabic-camelbert-ca-pos-egy | [
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"tf",
"bert",
"token-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
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"no_repeat... | 16,451 | null | ---
pipeline_tag: sentence-similarity
language: fr
datasets:
- stsb_multi_mt
tags:
- Text
- Sentence Similarity
- Sentence-Embedding
- camembert-base
license: apache-2.0
model-index:
- name: sentence-camembert-base by Van Tuan DANG
results:
- task:
name: Sentence-Embedding
type: Text Similarity
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CAMeL-Lab/bert-base-arabic-camelbert-ca-sentiment | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0"
] | text-classification | {
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"no_rep... | 73 | null | ---
language: en
tags:
- exbert
license: apache-2.0
datasets:
- bookcorpus
- wikipedia
---
# BERT base model (uncased)
## Model description
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1810.04805) and first released in
... | [
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CAMeL-Lab/bert-base-arabic-camelbert-ca | [
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"jax",
"bert",
"fill-mask",
"ar",
"arxiv:2103.06678",
"transformers",
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] | fill-mask | {
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"no_repeat_ngram_size... | 580 | null |
---
languages:
- as
- bn
- gu
- hi
- kn
- ml
- mr
- or
- pa
- ta
- te
tags:
- multilingual
- nlp
- indicnlp
widget:
- text: वैश्विक व्यापार युद्ध की शिकार हुई तुर्की की मुद्रा लीरा के डूबने से अमेरिकी डॉलर के मुकाबले रुपया अब तक के न्यूनतम स्तर पर पहुंच गया। रुपये में रिकॉर्ड गिरावट से सोने की चमक में निखार नहीं आ सकी... | [
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0.031365... |
CAMeL-Lab/bert-base-arabic-camelbert-da-poetry | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:1905.05700",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0"
] | text-classification | {
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],
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"no_rep... | 37 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: distilbert-imdb
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
args: plain_text
metrics:
- name: Accuracy
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CAMeL-Lab/bert-base-arabic-camelbert-da-pos-msa | [
"pytorch",
"tf",
"bert",
"token-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
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"no_repeat... | 27 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wmt16
metrics:
- bleu
model-index:
- name: punctuation-test-4
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: wmt16
type: wmt16
args: ro-en
metrics:
- ... | [
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CAMeL-Lab/bert-base-arabic-camelbert-da | [
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"tf",
"jax",
"bert",
"fill-mask",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
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],
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"no_repeat_ngram_size... | 449 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- cnn_dailymail
metrics:
- rouge
model-index:
- name: t5-small-finetuned-cnndm1
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: cnn_dailymail
type: cnn_dailymail
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CAMeL-Lab/bert-base-arabic-camelbert-mix-did-madar-corpus26 | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0"
] | text-classification | {
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"no_rep... | 45 | null | This model is a T5-3B reranker fine-tuned on the MS MARCO passage dataset for 10k steps (or 1 epoch).
For more details on how to use it, check [pygaggle.ai](pygaggle.ai)
Paper describing the model: [Document Ranking with a Pretrained Sequence-to-Sequence Model](https://www.aclweb.org/anthology/2020.findings-emnlp.63/... | [
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CAMeL-Lab/bert-base-arabic-camelbert-mix-did-nadi | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0"
] | text-classification | {
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"no_rep... | 63 | null | ---
language:
- es
tags:
- sentence similarity # Example: audio
- passage reranking # Example: automatic-speech-recognition
datasets:
- IIC/msmarco_es
metrics:
- eval_MRR@10: 0.688
model-index:
- name: roberta-base-bne-ranker
results:
- task:
type: text similarity # Required. Example: automatic-speech-r... | [
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CAMeL-Lab/bert-base-arabic-camelbert-mix-poetry | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:1905.05700",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0"
] | text-classification | {
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"no_rep... | 31 | null | ---
license: apache-2.0
language: fi
metrics:
- wer
- cer
tags:
- automatic-speech-recognition
- fi
- finnish
- generated_from_trainer
- hf-asr-leaderboard
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_7_0
model-index:
- name: wav2vec2-xlsr-1b-finnish-lm
results:
- task:
name: Automatic Sp... | [
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CAMeL-Lab/bert-base-arabic-camelbert-msa-pos-msa | [
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"tf",
"bert",
"token-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
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],
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"no_repeat... | 133 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: test-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. -->
#... | [
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CAMeL-Lab/bert-base-arabic-camelbert-msa-sixteenth | [
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"jax",
"bert",
"fill-mask",
"ar",
"arxiv:2103.06678",
"transformers",
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] | fill-mask | {
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"no_repeat_ngram_size... | 26 | null | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
language:
- es
datasets:
- hackathon-pln-es/nli-es
widget:
- text: "A ver si nos tenemos que poner todos en huelga hasta cobrar lo que queramos."
- text: "La huelga es el método de lucha más eficaz para conseg... | [
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CAUKiel/JavaBERT-uncased | [
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"safetensors",
"bert",
"fill-mask",
"java",
"code",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
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"no_repeat_ngram_size... | 7 | null | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: rare-puppers
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9285714030265808
---
# rare-puppers
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CAUKiel/JavaBERT | [
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"safetensors",
"bert",
"fill-mask",
"code",
"arxiv:2110.10404",
"arxiv:1910.09700",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
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"no_repeat_ngram_size... | 388 | 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
args: default... | [
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0.055505409836769104,
0.019755138084292412,
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0.03522925078868866,
0.0... |
CBreit00/DialoGPT_small_Rick | [] | null | {
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"num_beams... | 0 | null | ---
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: ita1
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. -->
# ita1
This model is a fin... | [
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CLAck/en-vi | [
"pytorch",
"marian",
"text2text-generation",
"en",
"vi",
"dataset:ALT",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | {
"architectures": [
"MarianMTModel"
],
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},
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"no_repeat_ngram_size... | 8 | null | ---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-german-cased-finetuned-subj
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and comp... | [
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CLAck/vi-en | [
"pytorch",
"marian",
"text2text-generation",
"en",
"vi",
"dataset:ALT",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | {
"architectures": [
"MarianMTModel"
],
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},
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"min_length": null,
"no_repeat_ngram_size... | 6 | null | <!-- Generated by scripts/utils/show_asr_result.sh -->
# RESULTS
## Environments
- date: `Mon Mar 21 22:59:35 UTC 2022`
- python version: `3.9.7 (default, Sep 16 2021, 13:09:58) [GCC 7.5.0]`
- espnet version: `espnet 0.10.7a1`
- pytorch version: `pytorch 1.10.1`
- Git hash: `7ae4efd81778436a98b822483e8123adba6aa430`
... | [
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CLS/WubiBERT_models | [] | null | {
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"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: bart-med-term-conditional-masking-0
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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CLTL/icf-levels-fac | [
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"text-classification",
"nl",
"transformers",
"license:mit"
] | text-classification | {
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"... | 32 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wav2vec2-base-finetuned-sentiment-mesd
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 remo... | [
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0.056... |
CLTL/icf-levels-stm | [
"pytorch",
"roberta",
"text-classification",
"nl",
"transformers",
"license:mit"
] | text-classification | {
"architectures": [
"RobertaForSequenceClassification"
],
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"... | 32 | null | ---
tags:
- generated_from_trainer
model-index:
- name: gpt2-xl_ft_logits_5k_experiment
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-xl_ft_logits_5k_ex... | [
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0.... |
CNT-UPenn/RoBERTa_for_seizureFrequency_QA | [
"pytorch",
"roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
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"RobertaForQuestionAnswering"
],
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},
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"min_length": null,
"no_re... | 5 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: gpt2-small-spanish-disco-poetry-15
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-jigsaw-severetoxic | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | {
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"BertForSequenceClassification"
],
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"no_rep... | 30 | null | ---
license: cc-by-4.0
---
This is the exported model for a small project I' working on, to test integration with spaces.
It is a fastai model and needs some custom code to work.
For now please ignore :) | [
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Camzure/MaamiBot | [] | null | {
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"num_beams... | 0 | null | ---
language:
- en
thumbnail: https://github.com/karanchahal/distiller/blob/master/distiller.jpg
tags:
- question-answering
license: apache-2.0
datasets:
- squad
metrics:
- squad
---
# DistilBERT with a second step of distillation
## Model description
This model replicates the "DistilBERT (D)" model from Table 2 of... | [
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Capreolus/birch-bert-large-msmarco_mb | [
"pytorch",
"tf",
"jax",
"bert",
"next-sentence-prediction",
"transformers"
] | null | {
"architectures": [
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],
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"no_rep... | 1 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-base-timit-demo-colab
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. -->
# wav2... | [
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Captain272/lstm | [] | null | {
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"num_beams... | 0 | null | ---
language: en
license: apache-2.0
tags:
- fill-mask
datasets:
- wikipedia
- bookcorpus
---
# 80% 1x4 Block Sparse BERT-Base (uncased) Prune OFA
This model is was created using Prune OFA method described in [Prune Once for All: Sparse Pre-Trained Language Models](https://arxiv.org/abs/2111.05754) presented in ENLSP... | [
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Cdial/hausa-asr | [
"wav2vec2",
"automatic-speech-recognition",
"ha",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | {
"architectures": [
"Wav2Vec2ForCTC"
],
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},
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"min_length": null,
"no_repeat_ngram_s... | 8 | null | ---
language: en
license: mit
tags:
- keyphrase-extraction
datasets:
- midas/inspec
metrics:
- seqeval
widget:
- text: "Keyphrase extraction is a technique in text analysis where you extract the important keyphrases from a document.
Thanks to these keyphrases humans can understand the content of a text very quickly a... | [
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Cedille/fr-boris | [
"pytorch",
"gptj",
"text-generation",
"fr",
"dataset:c4",
"arxiv:2202.03371",
"transformers",
"causal-lm",
"license:mit",
"has_space"
] | text-generation | {
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"GPTJForCausalLM"
],
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"no_repeat_ngram_size... | 401 | 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
args: plain_text
met... | [
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Chae/botman | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
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"no_repeat_ngram_size... | 5 | null | ```
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("BigSalmon/PointsToSentence")
model = AutoModelForCausalLM.from_pretrained("BigSalmon/PointsToSentence")
```
```
- moviepass to return
- this summer
- swooped up by
- original co-founder stacy spikes
text: the ... | [
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CharlieChen/feedback-bigbird | [] | null | {
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"num_beams... | 0 | null | ```
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("BigSalmon/InformalToFormalLincoln33")
model = AutoModelForCausalLM.from_pretrained("BigSalmon/InformalToFormalLincoln33")
```
```
- moviepass to return
- this summer
- swooped up by
- original co-founder stacy... | [
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Charlotte77/model_test | [] | null | {
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language: en
tags:
- tapex
- table-question-answering
datasets:
- wikitablequestions
license: mit
---
# TAPEX (base-sized model)
TAPEX was proposed in [TAPEX: Table Pre-training via Learning a Neural SQL Executor](https://arxiv.org/abs/2107.07653) by Qian Liu, Bei Chen, Jiaqi Guo, Morteza Ziyadi, Zeqi Lin, Weizh... | [
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ChaseBread/DialoGPT-small-harrypotter | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
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"GPT2LMHeadModel"
],
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"no_repeat_ngram_size... | 9 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
model-index:
- name: distilbert-base-uncased-finetuned-imdb
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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Cheatham/xlm-roberta-large-finetuned-r01 | [
"pytorch",
"xlm-roberta",
"text-classification",
"transformers"
] | text-classification | {
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"XLMRobertaForSequenceClassification"
],
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... | 23 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: finetuning-financial-news-sentiment
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 re... | [
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0.02... |
Cheatham/xlm-roberta-large-finetuned | [
"pytorch",
"xlm-roberta",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"XLMRobertaForSequenceClassification"
],
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... | 20 | null | ---
language:
- ja
license: cc-by-sa-4.0
datasets:
- wikipedia
- cc100
widget:
- text: "早稲田 大学 で 自然 言語 処理 を"
---
# nlp-waseda/gpt2-small-japanese
This model is Japanese GPT-2 pretrained on Japanese Wikipedia and CC-100.
## Intended uses & limitations
You can use the raw model for text generation or... | [
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Check/vaw2tmp | [
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] | null | {
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license: mit
tags:
- generated_from_trainer
model-index:
- name: codeparrot-ds-sample-2ep-29mar
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. -->
# codeparrot-... | [
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CheonggyeMountain-Sherpa/kogpt-trinity-punct-wrapper | [
"ko",
"gpt2",
"license:cc-by-nc-sa-4.0"
] | null | {
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"num_beams... | 0 | null | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: roomidentifier
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9375
---
# roomidentifier
Autogenerated ... | [
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Chertilasus/main | [] | null | {
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"num_beams... | 0 | null | ---
language: vi
datasets:
- vivos
- common_voice
metrics:
- wer
pipeline_tag: automatic-speech-recognition
tags:
- audio
- speech
- Transformer
license: cc-by-nc-4.0
model-index:
- name: Wav2vec2 NCKH Vietnamese 2022
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
data... | [
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Chikita1/www_stash_stock | [
"license:bsd-3-clause-clear"
] | null | {
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"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: codeparrot-ds-sample-gpt-small-neo
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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Chinmay/mlindia | [] | null | {
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"num_beams... | 0 | null | ---
license: bsd-3-clause
---
# Overview
The CodeGen model was proposed in by Erik Nijkamp, Bo Pang, Hiroaki Hayashi, Lifu Tu, Huan Wang, Yingbo Zhou, Silvio Savarese, and Caiming Xiong. From Salesforce Research.
The abstract from the paper is the following:
Program synthesis strives to generate a computer program a... | [
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ChoboAvenger/DialoGPT-small-joshua | [] | null | {
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"num_beams... | 0 | null | ---
language:
- es
- fr
- ru
- en
- it
tags:
- token-classification
- fill-mask
license: mit
datasets:
- iit-cdip
---
This model is the pretrained infoxlm checkpoint from the paper "LiLT: A Simple yet Effective Language-Independent Layout Transformer for Structured Document Understanding".
Original repository: http... | [
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ChrisP/xlm-roberta-base-finetuned-marc-en | [] | null | {
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license: mit
tags:
- generated_from_keras_callback
model-index:
- name: javilonso/classificationPolEsp1
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. -->
# javilonso... | [
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Chuah/DialoGPT-small-harrypotter | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"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... | 9 | 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
args: default... | [
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Chun/DialoGPT-medium-dailydialog | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
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"no_repeat_ngram_size... | 15 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: gpt-neo-therapist-small
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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0.0... |
Chun/w-zh2en-hsk | [
"pytorch",
"marian",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MarianMTModel"
],
"model_type": "marian",
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},
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"min_length": null,
"no_repeat_ngram_size... | 3 | null | ---
language:
- es
tags:
- question-answering # Example: audio
datasets:
- IIC/bioasq22_es
metrics:
- f1
# Optional. Add this if you want to encode your eval results in a structured way.
model-index:
- name: beto-base-cased-bioasq
results:
- task:
type: question-answering # Required. Example: automatic-spee... | [
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Chun/w-zh2en-mto | [
"pytorch",
"mbart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MBartForConditionalGeneration"
],
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},
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"max_length": null,
"min_length": null,
"no_re... | 7 | null | ---
language:
- es
tags:
- question-answering # Example: audio
datasets:
- IIC/bioasq22_es
metrics:
- f1
# Optional. Add this if you want to encode your eval results in a structured way.
model-index:
- name: roberta-base-bne-bioasq
results:
- task:
type: question-answering # Required. Example: automatic-spe... | [
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Chungu424/DATA | [] | null | {
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"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: javilonso/classificationEsp3_Attraction
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. -... | [
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Chungu424/qazwsx | [] | null | {
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"num_beams... | 0 | null | Fake news classifier
This model trains a text classification model to detect fake news articles,
it uses distilbert-base-uncased-finetuned-sst-2-english pretrained model to work on
fake and real news dataset from kaggle (https://www.kaggle.com/clmentbisaillon/fake-and-real-news-dataset) | [
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Chungu424/repo | [] | null | {
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language:
- code
license: mit
datasets:
- anjandash/java-8m-methods-v1
--- | [
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Cinnamon/electra-small-japanese-discriminator | [
"pytorch",
"electra",
"pretraining",
"ja",
"transformers",
"license:apache-2.0"
] | null | {
"architectures": [
"ElectraForPreTraining"
],
"model_type": "electra",
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"no_repeat_n... | 419 | 2022-03-30T12:29:04Z | ---
language:
- et
- en
- de
- ru
tags:
- translation
- modularNMT
- fairseq
- MTee
- crisis
inference: false
---
# MTee translation model for crisis domain
A crisis (mostly healthcare-related) domain translation model for the MTee machine translation platform. The platform was developed in 2021 as a collaboration b... | [
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Cinnamon/electra-small-japanese-generator | [
"pytorch",
"electra",
"fill-mask",
"ja",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"ElectraForMaskedLM"
],
"model_type": "electra",
"task_specific_params": {
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},
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"no_repeat_ngra... | 19 | 2022-03-30T12:29:20Z | ---
language:
- et
- en
- de
- ru
tags:
- translation
- modularNMT
- fairseq
- MTee
- military
inference: false
---
# MTee translation model for military domain
A military domain translation model for the MTee machine translation platform. The platform was developed in 2021 as a collaboration between the [TartuNLP](... | [
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Ciruzzo/DialoGPT-medium-harrypotter | [] | null | {
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"num_beams... | 0 | null | ---
language: es
license: cc-by-4.0
tags:
- spanish
- roberta
- bertin
pipeline_tag: text-classification
widget:
- text: La ciencia nos enseña, en efecto, a someter nuestra razón a la verdad y a conocer y juzgar las cosas como son, es decir, como ellas mismas eligen ser y no como quisiéramos que fueran.
---
# Readabil... | [
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Ciruzzo/DialoGPT-small-hattypotter | [] | null | {
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"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-base_toy_train_data_random_high_pass
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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0.0... |
Clarianliz30/Caitlyn | [] | null | {
"architectures": null,
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"num_beams... | 0 | 2022-03-30T13:41:58Z | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: javilonso/classificationPolEsp2
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. -->
# ja... | [
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ClydeWasTaken/DialoGPT-small-joshua | [
"conversational"
] | conversational | {
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},
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"num_beams... | 0 | 2022-03-30T14:51:24Z | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2hindiasr
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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0.042... |
CoShin/XLM-roberta-large_ko_en_nil_sts | [] | null | {
"architectures": null,
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"num_beams... | 0 | 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
args: default... | [
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CodeDanCode/CartmenBot | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
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"no_repeat_ngram_size... | 14 | 2022-04-09T16:43:00Z | ---
language: en
thumbnail: http://www.huggingtweets.com/tojibaceo/1654229333065/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; width... | [
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CodeNinja1126/test-model | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
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"no_rep... | 24 | 2022-03-30T15:40:23Z | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets: Sakonii/nepalitext-language-model-dataset
widget:
- text: नेपाल र भारतबीच
example_title: Example 1
- text: प्रधानमन्त्री
example_title: Example 2
- text: 'दस वर्ष लामो '
example_title: Example 3
- text: 'जापानमा आज '
example_title: Example 4
- tex... | [
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CoderEFE/DialoGPT-medium-marx | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
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"no_repeat_ngram_size... | 7 | 2022-03-30T17:35:24Z | ---
language: es
license: cc-by-4.0
tags:
- spanish
- roberta
- bertin
pipeline_tag: text-classification
widget:
- text: Las Líneas de Nazca son una serie de marcas trazadas en el suelo, cuya anchura oscila entre los 40 y los 110 centímetros.
- text: Hace mucho tiempo, en el gran océano que baña las costas del Perú no ... | [
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CoffeeAddict93/gpt1-call-of-the-wild | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
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"no_repeat_ngram_size... | 8 | null | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
language:
- es
datasets:
- hackathon-pln-es/parallel-sentences
widget:
- text: "A ver si nos tenemos que poner todos en huelga hasta cobrar lo que queramos."
- text: "La huelga es el método de l... | [
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CoffeeAddict93/gpt2-modest-proposal | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
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"no_repeat_ngram_size... | 12 | 2022-03-30T19:35:40Z | ---
tags:
- conversational
---
# Homer DialoGPT Model half data | [
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CogComp/bart-faithful-summary-detector | [
"pytorch",
"jax",
"bart",
"text-classification",
"en",
"dataset:xsum",
"transformers",
"xsum",
"license:cc-by-sa-4.0"
] | text-classification | {
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],
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"max_length": 128,
"min_length": 12,
"no_repeat_ng... | 234 | 2022-03-30T19:47:20Z | ---
license: apache-2.0
---
Upside down detection model for Fatima Fellowship Coding Challenge 2022 | [
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CohleM/bert-nepali-tokenizer | [] | null | {
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"num_beams... | 0 | 2022-03-30T19:55:28Z | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: poem-gen-spanish-t5-small-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. -->
# poem-gen-sp... | [
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Coldestadam/Breakout_Mentors_SpongeBob_Model | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
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},
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"no_repeat_ngram_size... | 10 | 2022-03-30T20:00:10Z | ---
language:
- en
tags:
- text-classification
widget:
- text: "I almost forgot to eat lunch.</s></s>I didn't forget to eat lunch."
- text: "I almost forgot to eat lunch.</s></s>I forgot to eat lunch."
- text: "I ate lunch.</s></s>I almost forgot to eat lunch."
datasets:
- alisawuffles/WANLI
---
This is an off-th... | [
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ComCom/gpt2-large | [
"pytorch",
"gpt2",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"GPT2Model"
],
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"no_repeat_ngram_size": nul... | 1 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-base-uncased-finetuned-mnli-rte-wnli-5
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... | [
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ComCom/gpt2 | [
"pytorch",
"gpt2",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"GPT2Model"
],
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},
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"min_length": null,
"no_repeat_ngram_size": nul... | 1 | null | ---
tags: autotrain
language: unk
widget:
- text: "I love AutoTrain 🤗"
datasets:
- vlsb/autotrain-data-security-texts-classification-roberta
co2_eq_emissions: 3.1151249696839685
---
# Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 688020754
- CO2 Emissions (in grams): 3.1151249696839... | [
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Contrastive-Tension/BERT-Large-CT-STSb | [
"pytorch",
"tf",
"jax",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
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"no_repeat_ngram_size": nul... | 7 | null | ---
language:
- en
inference:
parameters:
temperature: 0.7
top_p: 0.6
max_new_tokens: 64
num_return_sequences: 3
do_sample: true
license: apache-2.0
tags:
- QA
- medical
- gpt2
widget:
- text: "Question:What should gout patients pay attention to in diet? Answer:"
example_title: "test Que... | [
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Culmenus/opus-mt-de-is-finetuned-de-to-is_ancc | [] | null | {
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"num_beams... | 0 | null | ---
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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alexandrainst/da-hatespeech-detection-small | [
"pytorch",
"electra",
"text-classification",
"da",
"transformers",
"license:cc-by-4.0"
] | text-classification | {
"architectures": [
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],
"model_type": "electra",
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},
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"max_length": null,
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"... | 1,506 | null | ---
language: en
tags:
- lightweightgan
license: apache-2.0
datasets:
- glid3_orbs
---
# orbgan
lightweight GAN trained on my glid-3 orbs (https://huggingface.co/datasets/johnowhitaker/glid3_orbs) for demo I'm working on.
Training notebook: https://colab.research.google.com/drive/16o1TdrxnQ54Msbr813XfPVsnEt2QTRAa?us... | [
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Danih1502/t5-base-finetuned-en-to-de | [] | null | {
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"num_beams... | 0 | 2022-03-31T19:05:57Z | ---
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
args: default... | [
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Darein/Def | [] | null | {
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"num_beams... | 0 | 2022-03-31T19:44:47Z | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: rock-challenge-ViT-two-by-two
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9663800001144409
---
# rock... | [
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DarkKibble/DialoGPT-medium-Tankman | [] | null | {
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"num_beams... | 0 | 2022-02-21T11:50:09Z | ---
license: apache-2.0
---
# WellcomeBertMesh
WellcomeBertMesh is build from the data science team at the WellcomeTrust to tag biomedical grants with Medical Subject Headings ([Mesh](https://www.nlm.nih.gov/mesh/meshhome.html)). Even though developed with the intention to be used towards research grants, it sh... | [
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DarkWolf/kn-electra-small | [
"pytorch",
"electra",
"feature-extraction",
"transformers"
] | feature-extraction | {
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"BertModel"
],
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"no_repeat_ngram_size": ... | 4 | 2022-03-31T19:48:26Z | ---
language:
- en
license: cc-by-nc-4.0
tags:
- image-classification
- pytorch
datasets:
- nielsr/CelebA-faces
model-index:
- name: celebA_orientation_detection_model
results:
- task:
type: image_classification # Required. Example: automatic-speech-recognition
name: Image Classification # Opti... | [
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Darkrider/covidbert_medmarco | [
"pytorch",
"jax",
"bert",
"text-classification",
"arxiv:2010.05987",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
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"no_rep... | 35 | 2022-03-31T20:45:21Z | Preprocessing before feeding to model
```
from sentence_transformers import SentenceTransformer
model = SentenceTransformer('paraphrase-MiniLM-L6-v2', device='cuda')
...
embeddings = model.encode([text])
return embeddings[0]
``` | [
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DataikuNLP/average_word_embeddings_glove.6B.300d | [
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"sentence-transformers",
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"sentence-similarity",
"license:apache-2.0"
] | sentence-similarity | {
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"num_beams... | 0 | 2022-03-31T22:09:35Z | ---
tags:
- conversational
---
# Run 3 :)
# An exceedingly special thanks to Lynn Zheng for the tutorial on how to do this. | [
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"transformers",
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"no_repeat_ngram_size": nul... | 1,517 | 2022-03-31T23:51:06Z | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-base-uncased-finetuned-mnli-rte-wnli-10
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, the... | [
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Dave/twomad-model | [] | null | {
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"num_beams... | 0 | 2022-03-31T23:53:01Z | ---
tags:
- conversational
---
# Harry Potter Model | [
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DavidAMcIntosh/DialoGPT-small-rick | [] | null | {
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"num_beams... | 0 | null | ## This model is a fine-tuned version of distilbert-base-uncased-finetuned-sst-2-english on Fake and real dataset on kaggle
## The following hyperparameters were used during training:
learning_rate: 5e-05
train_batch_size: 8
num_epochs: 2
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DavidAMcIntosh/small-rick | [] | null | {
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"num_beams... | 0 | 2022-04-01T00:34:39Z | ---
language:
- pt
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: output
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to.... | [
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Davlan/bert-base-multilingual-cased-finetuned-amharic | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
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"no_repeat_ngram_size... | 109 | 2022-04-01T00:50:54Z | Glove Fake news Identification
This model is a fine-tuned of glove pre-trained model
In near future to be a fine-tuned of BERT and to make multiple comparisons based on updated tuning accuracy.
---
thumbnail: "https://miro.medium.com/max/600/0*a6XSwHsfvz_oWSSJ.jpg"
tags:
- python
- tensorflow
- Keras
- KerasT... | [
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... |
Davlan/bert-base-multilingual-cased-finetuned-luganda | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
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"no_repeat_ngram_size... | 16 | null | ---
language:
- en
thumbnail: https://github.com/karanchahal/distiller/blob/master/distiller.jpg
tags:
- question-answering
license: apache-2.0
datasets:
- squad
metrics:
- squad
---
# DistilBERT with a second step of distillation
## Model description
This model replicates the "DistilBERT (D)" model from Table 2 of... | [
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Davlan/distilbert-base-multilingual-cased-ner-hrl | [
"pytorch",
"tf",
"distilbert",
"token-classification",
"transformers",
"autotrain_compatible",
"has_space"
] | token-classification | {
"architectures": [
"DistilBertForTokenClassification"
],
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... | 123,856 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- null
model_index:
- name: bert-base-uncased-multi-128
results:
- task:
name: Masked Language Modeling
type: fill-mask
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
... | [
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... |
Davlan/xlm-roberta-base-finetuned-lingala | [
"pytorch",
"xlm-roberta",
"fill-mask",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"XLMRobertaForMaskedLM"
],
"model_type": "xlm-roberta",
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"no_repe... | 9 | null | ---
language:
- hu
tags:
- token-classification
license: apache-2.0
metrics:
- f1
widget:
- text: >-
A Kovácsné Nagy Erzsébet nagyon jól érzi magát a Nokiánál, azonban a
Németországból érkezett Kovács Péter nehezen boldogul a beilleszkedéssel.
---
# Hungarian Named Entity Recognition Model with huBERT
For fur... | [
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Davlan/xlm-roberta-base-finetuned-luo | [
"pytorch",
"xlm-roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
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"no_repe... | 5 | null | ---
tags:
- image-classification
- pytorch
- huggingpics
- llama-leaderboard
metrics:
- accuracy
model-index:
- name: llama-or-potato
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 1.0
---
# llama-or-pota... | [
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Davlan/xlm-roberta-base-finetuned-shona | [
"pytorch",
"xlm-roberta",
"fill-mask",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
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},
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"max_length": null,
"min_length": null,
"no_repe... | 5 | null | ---
tags:
- image-classification
- pytorch
- huggingpics
- llama-leaderboard
metrics:
- accuracy
model-index:
- name: llama-alpaca-snake
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.7910447716712952
--... | [
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0.0... |
Davlan/xlm-roberta-base-finetuned-zulu | [
"pytorch",
"xlm-roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"XLMRobertaForMaskedLM"
],
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"min_length": null,
"no_repe... | 3 | null | ---
tags:
- generated_from_trainer
model-index:
- name: sbert_large_nlu_ru-finetuned-squad-full
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. -->
# sbert_large_nlu... | [
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0.0... |
Davlan/xlm-roberta-base-sadilar-ner | [
"pytorch",
"xlm-roberta",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"XLMRobertaForTokenClassification"
],
"model_type": "xlm-roberta",
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"max_length": null,
"min_length": null,
... | 12 | null | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: ner-dummy-model
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. -->
# ner-dummy-model
T... | [
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0... |
Davlan/xlm-roberta-base-wikiann-ner | [
"pytorch",
"tf",
"xlm-roberta",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"XLMRobertaForTokenClassification"
],
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"min_length": null,
... | 235 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-irish-colab_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, ... | [
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Davlan/xlm-roberta-large-ner-hrl | [
"pytorch",
"tf",
"xlm-roberta",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"XLMRobertaForTokenClassification"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
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... | 1,322 | 2022-04-01T11:35:07Z | # poetry-generation-nextline-mbart-ws-fi-single
* `nextline`: generates a poem line from previous line(s)
* `mbart`: base model is [facebook/mbart-large-cc25](https://huggingface.co/facebook/mbart-large-cc25)
* `ws`: trained on Wikisource data
* `fi`: Finnish language
* `single`: uses only last poem line as input... | [
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Dazai/Ko | [] | null | {
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"num_beams... | 0 | null | ---
language: en
tags:
- classification
datasets:
- cifar10-custom
metrics:
- accuracy
---
# Up-Down Classification
This repo has the weights of resnet-18 model training on cifar-10 custom data, where some images are made upside down, and the goal is to predict the orientation of the image(0/1 classification task).... | [
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Dazai/Ok | [] | null | {
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"num_beams... | 0 | null | ---
tags:
- spacy
- token-classification
language:
- it
model-index:
- name: it_nerIta_trf
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.9196
- name: NER Recall
type: recall
value: 0.9086
- name: NER ... | [
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Dbluciferm3737/Idk | [] | null | {
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},
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"num_beams... | 0 | null | ---
tags:
- spacy
- token-classification
language:
- hu
license: cc-by-sa-4.0
model-index:
- name: hu_core_news_trf
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.909059294
- name: NER Recall
type: recall
... | [
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... |
DeadBeast/emoBERTTamil | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"dataset:tamilmixsentiment",
"transformers",
"generated_from_trainer",
"license:apache-2.0"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
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"max_length": null
},
"summarization": {
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"max_length": null,
"min_length": null,
"no_rep... | 35 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-sst2
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: sst2
metrics:
- ... | [
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0.0... |
Dean/summarsiation | [] | null | {
"architectures": null,
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},
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"num_beams... | 0 | 2022-04-01T12:58:00Z | TODO: This is still a demo model, the file does not match with the model card!!!
# poetry-generation-firstline-mbart-ws-fi-sorted
* `nextline`: generates the first poem line from keywords
* `mbart`: base model is [facebook/mbart-large-cc25](https://huggingface.co/facebook/mbart-large-cc25)
* `ws`: trained on Wikis... | [
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DecafNosebleed/DialoGPT-small-ScaraBot | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
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},
"summarization": {
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"min_length": null,
"no_repeat_ngram_size... | 15 | null | ---
language: en
license: mit
---
# HowTo QA with GPT-2 base
GPT-2 English language model fine-tuned with ±2.000 entries from WikiHow.
You can try it here: https://how-to-generator.herokuapp.com/
Input prompt should follow the following format:
`\n<|startoftext|>[WP] How to {text} \n[RESPONSE]`
Example:
`\n<|st... | [
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0.0... |
DecafNosebleed/scarabot-model | [
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
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"no_repeat_ngram_size... | 6 | 2022-04-01T13:17:05Z | ---
license: mit
tags:
- generated_from_trainer
datasets:
- indonlu
metrics:
- accuracy
- f1
model-index:
- name: indobert-classification
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: indonlu
type: indonlu
args: smsa
metrics:
- name: Ac... | [
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0.... |
Declan/FoxNews_model_v4 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
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},
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"min_length": null,
"no_repeat_ngram_size... | 7 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
model-index:
- name: distilbert-base-uncased-finetuned-emotion
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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0.0436... |
Declan/HuffPost_model_v3 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
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},
"summarization": {
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"min_length": null,
"no_repeat_ngram_size... | 3 | null | ---
language: "en"
tags:
- BigBird
- clinical
---
<span style="font-size:larger;">**Clinical-BigBird**</span> is a clinical knowledge enriched version of BigBird that was further pre-trained using MIMIC-III clinical notes. It allows up to 4,096 tokens as the model input. Clinical-BigBird consistently out-performs Cli... | [
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0... |
Declan/NPR_model_v1 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
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},
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"no_repeat_ngram_size... | 3 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: canine-c-finetuned-mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: mrpc
metrics:
- name: Accu... | [
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0.0... |
Declan/NPR_model_v2 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
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},
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"no_repeat_ngram_size... | 7 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-distilbert-fakenews-detection
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and co... | [
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0.026771150529384613,
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0.012745569460093975,
0.025436... |
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