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 |
|---|---|---|---|---|---|---|---|
Augustvember/WokkaBot5 | [] | null | {
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"num_beams... | 0 | null | ### Model information
* language : English
* fine tuning data : [squad 2.0](https://rajpurkar.github.io/SQuAD-explorer/)
* License : CC-BY-SA 4.0
* Base model : [xlm-roberta-base](https://huggingface.co/xlm-roberta-base)
* input : question, context
* output : answer
----
### Train information
* train_runt... | [
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Ayran/DialoGPT-small-harry-potter-1-through-3 | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
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"no_repeat_ngram_size... | 12 | null | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: glue-mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
type: glue
args: mrpc
metrics:
- name... | [
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Babelscape/rebel-large | [
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"transformers",
"seq2seq",
"relation-extraction",
"license:cc-by-nc-sa-4.0",
"model-index",
"autotrain_compatible",
"has_space"
] | text2text-generation | {
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],
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"no_repe... | 9,458 | null |
---
language: "en"
tags:
- neural-search-query-classification
- neural-search
widget:
- text: "keyword query."
---
# KEYWORD QUERY VS STATEMENT/QUESTION CLASSIFIER FOR NEURAL SEARCH
| Train Loss | Validation Acc.| Test Acc.|
| ------------- |:-------------: | -----: |
| 0.000806 | 0.99 | 0.997 |
```pyth... | [
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Babelscape/wikineural-multilingual-ner | [
"pytorch",
"tensorboard",
"safetensors",
"bert",
"token-classification",
"de",
"en",
"es",
"fr",
"it",
"nl",
"pl",
"pt",
"ru",
"multilingual",
"dataset:Babelscape/wikineural",
"transformers",
"named-entity-recognition",
"sequence-tagger-model",
"license:cc-by-nc-sa-4.0",
"aut... | token-classification | {
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"BertForTokenClassification"
],
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"no_repeat... | 41,608 | null | # A Multi-task learning model with two prediction heads
* One prediction head classifies between keyword sentences vs statements/questions
* Other prediction head corresponds to classifier for statements vs questions
## Scores
##### Spaadia SQuaD Test acc: **0.9891**
##### Quora Keyword Pairs Test acc: **0.98048**
##... | [
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Babysittingyoda/DialoGPT-small-familyguy | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
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"no_repeat_ngram_size... | 13 | null | The distilbart-cnn-12-6-text2sql is fine-tuned on WIKISQL dataset.
```python
from transformers import BartTokenizer, BartForConditionalGeneration, BartConfig
model = BartForConditionalGeneration.from_pretrained('shahrukhx01/distilbart-cnn-12-6-text2sql')
tokenizer = BartTokenizer.from_pretrained('shahrukhx01/distilbar... | [
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Backedman/DialoGPT-small-Anika | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
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],
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"no_repeat_ngram_size... | 6 | null | ---
tags:
- fuzzy-matching
- fuzzy-search
- entity-resolution
- record-linking
- structured-data-search
---
A Siamese BERT architecture trained at character levels tokens for embedding based Fuzzy matching.
## Usage (Sentence-Transformers)
Using this model becomes easy when you have [sentence-transformers](https://ww... | [
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Badr/model1 | [] | null | {
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"num_beams... | 0 | null | ---
language: "en"
tags:
- neural-search-query-classification
- neural-search
widget:
- text: "what did you eat in lunch?"
---
# KEYWORD STATEMENT VS QUESTION CLASSIFIER FOR NEURAL SEARCH
```python
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained(... | [
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Bagus/SER-LSSED | [] | null | {
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"num_beams... | 0 | null | ---
language: "en"
tags:
- boolean-qa
widget:
- text: "Is Berlin the smallest city of Germany? <s> Berlin is the capital and largest city of Germany by both area and population. Its 3.8 million inhabitants make it the European Union's most populous city, according to the population within city limits "
---
# Labels Ma... | [
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Bagus/ser-japanese | [] | null | {
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"num_beams... | 0 | null | ## Multiple Prediction Heads
* ExtractiveQA Head
* Three Class Classification Head, classes => (yes, no, extra_qa) to answer binary questions or direct to ExtractiveQA Head
## BoolQ Validation dataset Evaluation: <br/>
support => 3270 <br/>
accuracy => 0.73 <br/>
macro f1 => 0.71
## SQuAD Validation dataset Evaluati... | [
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Bagus/wav2vec2-large-xlsr-bahasa-indonesia | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"el",
"dataset:common_voice_id_6.1",
"transformers",
"audio",
"speech",
"bahasa-indonesia",
"license:apache-2.0"
] | automatic-speech-recognition | {
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],
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"no_repeat_ngram_s... | 12 | 2021-08-18T20:11:10Z | ---
language: "en"
tags:
- schema-aware-text2sql
- text2sql
- wikisql
widget:
- text: "What is terrence ross' nationality? </s> <col0> Player : text <col1> No. : text <col2> Nationality : text <col3> Position : text <col4> Years in Toronto : text <col5> School/Club Team : text"
---
```python
from transformers import B... | [
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Bagus/wav2vec2-xlsr-greek-speech-emotion-recognition | [
"pytorch",
"tensorboard",
"wav2vec2",
"el",
"dataset:aesdd",
"transformers",
"audio",
"audio-classification",
"speech",
"license:apache-2.0"
] | audio-classification | {
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],
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"... | 21 | 2021-08-12T06:10:50Z | ---
tags:
- wikisql
- text2sql
---
```python
from transformers import BartTokenizer, BartForConditionalGeneration, BartConfig
model = BartForConditionalGeneration.from_pretrained('shahrukhx01/schema-aware-distilbart-cnn-12-6-text2sql')
tokenizer = BartTokenizer.from_pretrained('shahrukhx01/schema-aware-distilbart-cnn-1... | [
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Balgow/prod_desc | [] | null | {
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"num_beams... | 0 | 2022-02-18T18:41:25Z | # wav2vec2-xls-r-1b-dv-with-lm
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the common_voice dataset. | [
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Barbarameerr/Barbara | [] | null | {
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"num_beams... | 0 | null | ---
tags:
- generated_from_trainer
widget:
- text: "What is COVID-19?"
context: "Coronavirus disease 2019 (COVID-19) is a contagious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The first known case was identified in Wuhan, China, in December 2019.[7] The disease has since spread wo... | [
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Barleysack/klue-roberta-LSTM | [
"pytorch",
"roberta",
"transformers"
] | null | {
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],
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"no_repeat_ngram_s... | 6 | 2021-11-19T15:38:21Z | ---
license: apache-2.0
tags:
- generated_from_trainer
- summarization
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-arxiv-cs-finetuned-arxiv-cs-full
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread... | [
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BatuhanYilmaz/bert-finetuned-ner | [] | null | {
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"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: t5-base-fine-tuned-for-Punctuation-Restoration
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
---
<!-- This model card has been generated automatically according to the information the ... | [
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Baybars/wav2vec2-xls-r-300m-cv8-turkish | [
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"wav2vec2",
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"tr",
"dataset:common_voice",
"transformers",
"common_voice",
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"robust-speech-event",
"license:apache-2.0"
] | automatic-speech-recognition | {
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],
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"no_repeat_ngram_s... | 5 | null | ---
tags:
- conversational
---
# Ash DialoGPT Model | [
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BigSalmon/FormalBerta2 | [
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] | fill-mask | {
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"no_repeat_ngra... | 16 | null | ---
Language Pair Finetuned:
- en-mr
Metrics:
- sacrebleu
- WAT 2021: 16.11
# mbart-large-finetuned-en-mr
## Model Description
This is the mbart-large-50 model finetuned on En-Mr corpus.
## Intended uses and limitations
Mostly useful for English to Marathi translation but the mbart-large-50 model also suppor... | [
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BigSalmon/GPT2HardandEasy | [
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"tensorboard",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
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"no_repeat_ngram_size... | 9 | 2022-01-28T17:28:25Z | ---
language:
- hi
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: ''
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You... | [
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0.0... |
BigSalmon/GPTHeHe | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"has_space"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
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"no_repeat_ngram_size... | 8 | 2022-01-27T13:04:19Z | ---
language:
- mr
license: apache-2.0
tags:
- automatic-speech-recognition
- generated_from_trainer
- hf-asr-leaderboard
- mozilla-foundation/common_voice_8_0
- mr
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: ''
results:
- task:
type: automatic-speech-recognition... | [
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BigSalmon/InformalToFormalLincoln20 | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
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"no_repeat_ngram_size... | 8 | null | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: vision-transformer-fmri-classification-ft
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.7955589294433594... | [
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BigSalmon/MrLincoln6 | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
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"no_repeat_ngram_size... | 9 | null | ---
language:
- tr
license: apache-2.0
tags:
- automatic-speech-recognition
- common_voice
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-common_voice-tr-demo
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to.... | [
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BigSalmon/NEO125InformalToFormalLincoln | [
"pytorch",
"gpt_neo",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPTNeoForCausalLM"
],
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"no_repeat_ngram... | 8 | null | # ELECTRA-small-OWT
This is an unnoficial implementation of an
[ELECTRA](https://openreview.net/forum?id=r1xMH1BtvB) small model, trained on the
[OpenWebText corpus](https://skylion007.github.io/OpenWebTextCorpus/).
Differences from official ELECTRA models:
- we use a `BertForMaskedLM` as the generator and `BertForT... | [
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0.05... |
BigSalmon/ParaphraseParentheses | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
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},
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"min_length": null,
"no_repeat_ngram_size... | 10 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: mrpc
metrics:
... | [
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0.0... |
BillelBenoudjit/jplu-wikiann | [
"fr",
"dataset:wikiann",
"model-index"
] | null | {
"architectures": null,
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"num_beams... | 0 | 2022-02-02T05:34:19Z | ---
language:
- et
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- robust-speech-event
- et
- hf-asr-leaderboard
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: xls-r-et-cv_8_0
results:
- task:
name: Automatic Speec... | [
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Bilz/DialoGPT-small-harrypotter | [] | null | {
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"num_beams... | 0 | 2022-01-27T23:14:34Z | ---
language:
- et
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_7_0
- generated_from_trainer
- robust-speech-event
- et
- hf-asr-leaderboard
datasets:
- mozilla-foundation/common_voice_7_0
model-index:
- name: ''
results:
- task:
name: Automatic Speech Recognition... | [
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Bimal/my_bot_model | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
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"GPT2LMHeadModel"
],
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"no_repeat_ngram_size... | 10 | 2022-02-06T04:21:10Z | ---
language:
- eu
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- robust-speech-event
- et
- hf-asr-leaderboard
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: xls-r-eus
results:
- task:
name: Automatic Speech Reco... | [
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Binbin/test | [] | null | {
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"num_beams... | 0 | 2021-07-07T11:52:20Z | ---
thumbnail: https://huggingface.co/front/thumbnails/dialogpt.png
tags:
- conversational
license: mit
---
# DialoGPT Trained on WhatsApp chats
This is an instance of [microsoft/DialoGPT-medium](https://huggingface.co/microsoft/DialoGPT-medium) trained on WhatsApp chats or you can train this model on [a Kaggle game sc... | [
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BinksSachary/DialoGPT-small-shaxx | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
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"min_length": null,
"no_repeat_ngram_size... | 12 | null | ---
thumbnail: https://huggingface.co/front/thumbnails/dialogpt.png
tags:
- conversational
license: mit
---
# DialoGPT Trained on WhatsApp chats
This is an instance of [microsoft/DialoGPT-medium](https://huggingface.co/microsoft/DialoGPT-medium) trained on WhatsApp chats or you can train this model on [a Kaggle game sc... | [
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BinksSachary/ShaxxBot | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
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"no_repeat_ngram_size... | 9 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wav2vec2-large-xls-r-300m-dementianet
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 remov... | [
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BitanBiswas/mbert-bengali-ner-finetuned-ner | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
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"max_length": null
},
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"min_length": null,
"no_repeat... | 4 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wav2vec2-large-xls-r-300m-dm32
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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Blabla/Pipipopo | [] | null | {
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"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wav2vec2-large-xls-r-300m-sanitycheck
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 remov... | [
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Blackmist786/DialoGPt-small-transformers4 | [
"pytorch"
] | null | {
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"num_beams... | 4 | null | # shrugging-grace/tweetclassifier
## Model description
This model classifies tweets as either relating to the Covid-19 pandemic or not.
## Intended uses & limitations
It is intended to be used on tweets commenting on UK politics, in particular those trending with the #PMQs hashtag, as this refers to weekly Prime Min... | [
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Blazeolmo/Scrabunzi | [] | null | {
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"num_beams... | 0 | null | Longformer-large model finetuned for the coreference resolution task. The model is fine-tuned over a mixture of OntoNotes, LitBank, and PreCo. The model is released as part of [this paper](https://arxiv.org/pdf/2109.09667.pdf). Note that the document encoder is to be used with the rest of the model parameters to perfor... | [
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Blerrrry/Kkk | [] | null | {
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"num_beams... | 0 | 2021-11-07T16:12:06Z | Longformer-large model finetuned for the coreference resolution task. The model is fine-tuned over the OntoNotes data. The model is released as part of [this paper](https://arxiv.org/pdf/2109.09667.pdf). Note that the document encoder is to be used with the rest of the model parameters to perform the coreference resolu... | [
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BlindMan820/Sarcastic-News-Headlines | [
"pytorch",
"distilbert",
"text-classification",
"English",
"dataset:Kaggle Dataset",
"transformers",
"Text",
"Sequence-Classification",
"Sarcasm",
"DistilBert"
] | text-classification | {
"architectures": [
"DistilBertForSequenceClassification"
],
"model_type": "distilbert",
"task_specific_params": {
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},
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... | 28 | 2022-02-19T04:31:10Z | ---
license: apache-2.0
---
AIShell transducer stateless CER is 5.04% | [
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Bloodwarrior/Chikfalay | [] | null | {
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"num_beams... | 0 | null | # Steps to use this model
This model uses tokenizer 'rinna/japanese-roberta-base'. Therefore, below steps are critical to run the model correctly.
1. Create a local root directory on your system and new python environment.
2. Install below requirements
```
transformers==4.12.2
torch==1.10.0
numpy==1.21.3
pandas==1.3... | [
-0.02060171589255333,
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0.06890863925218582,
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0.0... |
BlueGamerBeast/DialoGPT-small-joshua | [] | null | {
"architectures": null,
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"num_beams... | 0 | null | # BriVL
BriVL (Bridging Vision and Language Model) 是首个中文通用图文多模态大规模预训练模型。BriVL模型在图文检索任务上有着优异的效果，超过了同期其他常见的多模态预训练模型（例如UNITER、CLIP）。
BriVL论文：[WenLan: Bridging Vision and Language by Large-Scale Multi-Modal Pre-Training](https://arxiv.org/abs/2103.06561)
# 适用场景
适用场景示例：图像检索文本、文本检索图像、图像标注、图像零样本分类、作为其他下游多模态任务的输入特征等。
# ... | [
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... |
BobBraico/distilbert-base-uncased-finetuned-imdb-accelerate | [] | null | {
"architectures": null,
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"num_beams... | 0 | 2021-09-18T10:27:44Z | # Less is More: Pre-train a Strong Text Encoder for Dense Retrieval Using a Weak Decoder
Please check the [official repository](https://github.com/microsoft/SEED-Encoder) for more details and updates.
# Fine-tuning on Marco passage/doc ranking tasks and NQ tasks
| MSMARCO Dev Passage Retrieval | MRR@10 | Reca... | [
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0... |
BrianTin/MTBERT | [
"pytorch",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
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},
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"no_repeat_ngram_size... | 11 | 2020-12-16T19:00:12Z | ---
language:
- ur
tags:
- urdu
- language-model
license: mit
datasets:
- urdu-text-news
---
| [
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Brinah/1 | [] | null | {
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"num_beams... | 0 | 2021-08-09T21:33:49Z | ---
tags:
- generated_from_trainer
datasets:
- gem
model_index:
- name: BART-commongen
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: gem
type: gem
args: common_gen
---
<!-- This model card has been generated automatically a... | [
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0.032... |
BritishLibraryLabs/bl-books-genre | [
"pytorch",
"distilbert",
"text-classification",
"multilingual",
"dataset:blbooksgenre",
"transformers",
"genre",
"books",
"library",
"historic",
"glam ",
"lam",
"license:mit",
"has_space"
] | text-classification | {
"architectures": [
"DistilBertForSequenceClassification"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
... | 76 | 2021-08-10T01:25:30Z | ---
license: mit
tags:
- generated_from_trainer
datasets:
- gem
model_index:
- name: BART-large-commongen
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: gem
type: gem
args: common_gen
---
<!-- This model card has been genera... | [
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-0.011084320023655891,
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... |
Broadus20/DialoGPT-small-joshua | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 12 | null | ## Tokenizer for the python code trained on GPT-2 model | [
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0... |
BrunoNogueira/DialoGPT-kungfupanda | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
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"conversational": {
"max_length": 1000
},
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"no_repeat_ngram_size... | 10 | null | ---
language: "en"
tags:
- sentiment
- twitter
- reviews
- siebert
---
## SiEBERT - English-Language Sentiment Classification
# Overview
This model ("SiEBERT", prefix for "Sentiment in English") is a fine-tuned checkpoint of [RoBERTa-large](https://huggingface.co/roberta-large) ([Liu et al. 2019](https://arxiv.org/pd... | [
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0.... |
Bryan190/Aguy190 | [] | null | {
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"num_beams... | 0 | null | ---
tags:
- conversational
---
#Harry Potter DialoGPT Model | [
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BumBelDumBel/TRUMP | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers",
"generated_from_trainer",
"license:mit"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
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},
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"no_repeat_ngram_size... | 5 | null | # deep-todo
Wondering what to do? Not anymore!
Generate arbitrary todo's.
Source: <https://colab.research.google.com/drive/1PlKLrGHaCuvWCKNC4fmQEMElF-iRec9f?usp=sharing>
The todo's come from a random selection of (public) repositories I had on my computer.
### Sample
A bunch of todo's:
```
---------------------... | [
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0.009435591287910938,
0.006643290631473064,
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0.004083427134901285,
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0.059094980359077454,
0.028184588998556137,
-0.004206607583910227,
0.014531834982335567,
0... |
BumBelDumBel/ZORK_AI_FANTASY | [] | null | {
"architectures": null,
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},
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"num_beams... | 0 | null | ---
license: cc-by-sa-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: model1_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. -->... | [
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0.0... |
Buntan/bert-finetuned-ner | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"dataset:conll2003",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 8 | null | - You'll need to instantiate a special RoBERTa class. Though technically a "Longformer", the elongated RoBERTa model will still need to be pulled in as such.
- To do so, use the following classes:
```python
class RobertaLongSelfAttention(LongformerSelfAttention):
def forward(
self,
hidden_states,
... | [
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0... |
CLTL/icf-levels-etn | [
"pytorch",
"roberta",
"text-classification",
"nl",
"transformers",
"license:mit"
] | text-classification | {
"architectures": [
"RobertaForSequenceClassification"
],
"model_type": "roberta",
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"... | 31 | null | ---
language:
- ru
tags:
- toxic comments classification
---
## RuBERT-Toxic
RuBERT-Toxic is a [RuBERT](https://huggingface.co/DeepPavlov/rubert-base-cased) model fine-tuned on [Kaggle Russian Language Toxic Comments Dataset](https://www.kaggle.com/blackmoon/russian-language-toxic-comments). You can find a detailed ... | [
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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 | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 145 | null | ---
language:
- ru
tags:
- sentiment analysis
- Russian
---
## XLM-RoBERTa-Base-ru-sentiment-RuReviews
XLM-RoBERTa-Base-ru-sentiment-RuReviews is a [XLM-RoBERTa-Base](https://huggingface.co/xlm-roberta-base) model fine-tuned on [RuReviews dataset](https://github.com/sismetanin/rureviews) of Russian-language reviews ... | [
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0.03... |
CallumRai/HansardGPT2 | [
"pytorch",
"jax",
"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... | 14 | null | ---
language:
- ru
tags:
- sentiment analysis
- Russian
---
## XML-RoBERTa-Base-ru-sentiment-RuSentiment
XML-RoBERTa-Base-ru-sentiment-RuSentiment is a [XML-RoBERTa-Base](https://huggingface.co/xlm-roberta-base) model fine-tuned on [RuSentiment dataset](https://github.com/text-machine-lab/rusentiment) of general-dom... | [
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0.... |
dccuchile/albert-tiny-spanish-finetuned-mldoc | [
"pytorch",
"albert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"AlbertForSequenceClassification"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no... | 32 | null | ---
language: hi
datasets:
- common_voice
- indic tts
- iiith
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: Hindi XLSR Wav2Vec2 Large 53
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dat... | [
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... |
dccuchile/bert-base-spanish-wwm-uncased-finetuned-ner | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 5 | null | ---
tags:
- conversational
---
# Rick DialoGPT Model | [
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0.040... |
Certified-Zoomer/DialoGPT-small-rick | [] | null | {
"architectures": null,
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},
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"num_beams... | 0 | null | ---
language:
- "ko"
---
## KoRean based ELECTRA (KR-ELECTRA)
This is a release of a Korean-specific ELECTRA model with comparable or better performances developed by the Computational Linguistics Lab at Seoul National University. Our model shows remarkable performances on tasks related to informal texts such as r... | [
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Chaima/TunBerto | [] | null | {
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"num_beams... | 0 | null | # Multilingual Joint Fine-tuning of Transformer models for identifying Trolling, Aggression and Cyberbullying at TRAC 2020
Models and predictions for submission to TRAC - 2020 Second Workshop on Trolling, Aggression and Cyberbullying.
Our trained models as well as evaluation metrics during traing are available at: ht... | [
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0.05275849997997284,
0.05223928764462471,
-0.026563353836536407,
0.012405665591359138,
... |
Chakita/Kalbert | [
"pytorch",
"tensorboard",
"albert",
"fill-mask",
"transformers",
"generated_from_trainer",
"license:mit",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"AlbertForMaskedLM"
],
"model_type": "albert",
"task_specific_params": {
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},
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"min_length": null,
"no_repeat_ngram_... | 5 | null | # Multilingual Joint Fine-tuning of Transformer models for identifying Trolling, Aggression and Cyberbullying at TRAC 2020
Models and predictions for submission to TRAC - 2020 Second Workshop on Trolling, Aggression and Cyberbullying.
Our trained models as well as evaluation metrics during traing are available at: ht... | [
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Chakita/KannadaBERT | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"masked-lm",
"fill-in-the-blanks",
"autotrain_compatible"
] | fill-mask | {
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],
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"no_repeat_ngra... | 5 | null | # Multilingual Joint Fine-tuning of Transformer models for identifying Trolling, Aggression and Cyberbullying at TRAC 2020
Models and predictions for submission to TRAC - 2020 Second Workshop on Trolling, Aggression and Cyberbullying.
Our trained models as well as evaluation metrics during traing are available at: ht... | [
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Chakita/gpt2_mwp | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
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"min_length": null,
"no_repeat_ngram_size... | 6 | null | # Multilingual Joint Fine-tuning of Transformer models for identifying Trolling, Aggression and Cyberbullying at TRAC 2020
Models and predictions for submission to TRAC - 2020 Second Workshop on Trolling, Aggression and Cyberbullying.
Our trained models as well as evaluation metrics during traing are available at: ht... | [
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Chalponkey/DialoGPT-small-Barry | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
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},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 11 | null | # Multilingual Joint Fine-tuning of Transformer models for identifying Trolling, Aggression and Cyberbullying at TRAC 2020
Models and predictions for submission to TRAC - 2020 Second Workshop on Trolling, Aggression and Cyberbullying.
Our trained models as well as evaluation metrics during traing are available at: ht... | [
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Cheatham/xlm-roberta-large-finetuned3 | [
"pytorch",
"xlm-roberta",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"XLMRobertaForSequenceClassification"
],
"model_type": "xlm-roberta",
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},
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... | 22 | null | # rdr-queston_encoder-single-nq-base
Reader-Distilled Retriever (`RDR`)
Sohee Yang and Minjoon Seo, [Is Retriever Merely an Approximator of Reader?](https://arxiv.org/abs/2010.10999), arXiv 2020
The paper proposes to distill the reader into the retriever so that the retriever absorbs the strength of the reader while... | [
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Cheatham/xlm-roberta-large-finetuned4 | [
"pytorch",
"xlm-roberta",
"text-classification",
"transformers"
] | text-classification | {
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],
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... | 20 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: chinese-bert-wwm-chinese_bert_wwm1
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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Chuah/DialoGPT-small-harrypotter | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
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},
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"min_length": null,
"no_repeat_ngram_size... | 9 | null | ---
language: ja
tags:
- byt5
- t5
- text2text-generation
- seq2seq
license: cc-by-sa-4.0
datasets:
- wikipedia
- oscar
- cc100
---
# 日本語ByT5事前学習済みモデル
This is a [ByT5 (a tokenizer-free extension of the Text-to-Text Transfer Transformer)](https://github.com/google-research/byt5/) model pretrained on Japanese corpus.
... | [
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Chun/DialoGPT-medium-dailydialog | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
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"GPT2LMHeadModel"
],
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"no_repeat_ngram_size... | 15 | null | ---
language: ja
license: cc-by-sa-4.0
tags:
- sentence-transformers
- sentence-bert
- feature-extraction
- sentence-similarity
---
This is a Japanese sentence-BERT model.
日本語用Sentence-BERTモデル（バージョン1）です。
※: 精度が1.5ポイントほど向上した[バージョン2モデル](https://huggingface.co/sonoisa/sentence-bert-base-ja-mean-tokens-v2)もあります。
# 解説
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Chungu424/repodata | [] | null | {
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"num_beams... | 0 | 2021-10-14T16:05:42Z | ---
license: mit
tags:
- generated_from_trainer
datasets:
- squad_v2
model-index:
- name: xlm-roberta-large-finetuned-squad-v2_15102021
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 rem... | [
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Chuu/Chumar | [] | null | {
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"num_beams... | 0 | null | ---
tags:
- generated_from_trainer
datasets:
- squad
model-index:
- name: xlm-roberta-large-finetuned-squad
results:
- task:
name: Question Answering
type: question-answering
dataset:
name: squad
type: squad
args: default
---
<!-- This model card has been generated automatically a... | [
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CodeDanCode/SP-KyleBot | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
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"GPT2LMHeadModel"
],
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"no_repeat_ngram_size... | 15 | null | ---
tags:
- spacy
- token-classification
language:
- ca
license: gpl-3.0
model-index:
- name: ca_core_news_md
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.8433931485
- name: NER Recall
type: recall
value... | [
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CodeNinja1126/koelectra-model | [] | null | {
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"num_beams... | 0 | null | ---
tags:
- spacy
- token-classification
language:
- da
license: cc-by-sa-4.0
model-index:
- name: da_core_news_md
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.8020833333
- name: NER Recall
type: recall
... | [
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Venkatakrishnan-Ramesh/Text_gen | [] | null | {
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"num_beams... | 0 | 2021-07-07T10:27:30Z | ---
tags:
- spacy
- token-classification
language:
- de
license: mit
model-index:
- name: de_dep_news_trf
results:
- task:
name: TAG
type: token-classification
metrics:
- name: TAG (XPOS) Accuracy
type: accuracy
value: 0.990643584
- task:
name: POS
type: token-classific... | [
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CoffeeAddict93/gpt2-call-of-the-wild | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
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"no_repeat_ngram_size... | 6 | 2021-07-07T12:39:26Z | ---
tags:
- spacy
- token-classification
language:
- el
license: cc-by-nc-sa-3.0
model-index:
- name: el_core_news_sm
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.742081448
- name: NER Recall
type: recall
... | [
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CoffeeAddict93/gpt2-medium-call-of-the-wild | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
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},
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"no_repeat_ngram_size... | 14 | null | ---
tags:
- spacy
- token-classification
language:
- en
license: mit
model-index:
- name: en_core_web_lg
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.8516398746
- name: NER Recall
type: recall
value: 0.8... | [
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ComCom/gpt2-medium | [
"pytorch",
"gpt2",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"GPT2Model"
],
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},
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"no_repeat_ngram_size": nul... | 5 | null | ---
tags:
- spacy
- token-classification
language:
- fr
license: lgpl-lr
model-index:
- name: fr_core_news_md
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.8317031703
- name: NER Recall
type: recall
value... | [
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ComCom/gpt2 | [
"pytorch",
"gpt2",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"GPT2Model"
],
"model_type": "gpt2",
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},
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"no_repeat_ngram_size": nul... | 1 | 2021-07-07T12:32:58Z | ---
tags:
- spacy
- token-classification
language:
- fr
license: lgpl-lr
model-index:
- name: fr_core_news_sm
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.8148438757
- name: NER Recall
type: recall
value... | [
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Connor-tech/bert_cn_finetuning | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
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},
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"no_rep... | 27 | 2021-07-07T12:08:11Z | ---
tags:
- spacy
- token-classification
language:
- ja
license: cc-by-sa-4.0
model-index:
- name: ja_core_news_lg
results:
- task:
name: NER
type: token-classification
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Connorvr/TeachingGen | [
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tags:
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license: cc-by-sa-4.0
model-index:
- name: ja_core_news_sm
results:
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name: NER
type: token-classification
metrics:
- name: NER Precision
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ConstellationBoi/Oop | [] | null | {
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"num_beams... | 0 | 2021-11-09T16:58:01Z | ---
tags:
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language:
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license: cc-by-sa-3.0
model-index:
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results:
- task:
name: NER
type: token-classification
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Contrastive-Tension/BERT-Large-CT-STSb | [
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"no_repeat_ngram_size": nul... | 7 | 2021-07-07T12:00:43Z | ---
tags:
- spacy
- token-classification
language:
- nb
license: mit
model-index:
- name: nb_core_news_md
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.811827957
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type: recall
value: 0.8... | [
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CouchCat/ma_ner_v7_distil | [
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"en",
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... | 13 | 2021-07-07T10:48:04Z | ---
tags:
- spacy
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language:
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license: cc-by-sa-4.0
model-index:
- name: ro_core_news_sm
results:
- task:
name: NER
type: token-classification
metrics:
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type: precision
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type: recall
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CouchCat/ma_sa_v7_distil | [
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... | 38 | null | ---
tags:
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language:
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license: mit
model-index:
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results:
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name: NER
type: token-classification
metrics:
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CoveJH/ConBot | [] | null | {
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"num_beams... | 0 | 2021-07-07T10:44:17Z | ---
tags:
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Coverage/sakurajimamai | [] | null | {
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tags:
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model-index:
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Coyotl/DialoGPT-test-last-arthurmorgan | [
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"num_beams... | 0 | 2021-07-07T10:35:50Z | ---
tags:
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language:
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license: mit
model-index:
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results:
- task:
name: NER
type: token-classification
metrics:
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Coyotl/DialoGPT-test3-arthurmorgan | [
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"num_beams... | 0 | 2021-07-07T10:31:39Z | ---
tags:
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language:
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license: mit
model-index:
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results:
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name: NER
type: token-classification
metrics:
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CracklesCreeper/Piglin-Talks-Harry-Potter | [
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] | conversational | {
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"no_repeat_ngram_size... | 10 | null | ---
tags:
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license: mit
model-index:
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results:
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name: NER
type: token-classification
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CrayonShinchan/fine_tune_try_1 | [] | null | {
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"num_beams... | 0 | 2021-10-25T13:59:49Z | ---
language: en
license: mit
---
Import it using pipeline
from transformers import pipeline
text_generation = pipeline('text-generation' , model='sparki/kinkyfurs-gpt2')
Then use it
prefix_text = input()
text_generation(prefix_text, max_length=50, num_beams=5,no_repeat_ngram_size=2,early_s... | [
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CrypticT1tan/DialoGPT-medium-harrypotter | [] | null | {
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tags:
- generated_from_trainer
datasets:
- librispeech_asr
model-index:
- name: ''
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. -->
#
This model was trained... | [
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Crystal/distilbert-base-uncased-finetuned-squad | [] | null | {
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tags:
- generated_from_trainer
datasets:
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model-index:
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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. -->
#
This model was trained... | [
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Culmenus/IceBERT-finetuned-ner | [
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"no_... | 5 | 2022-02-14T15:05:22Z | ---
tags:
- generated_from_trainer
datasets:
- librispeech_asr
model-index:
- name: ''
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. -->
#
This model was trained... | [
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Culmenus/checkpoint-168500-finetuned-de-to-is_nr2 | [] | null | {
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tags:
- generated_from_trainer
datasets:
- librispeech_asr
model-index:
- name: ''
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. -->
#
This model was trained... | [
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Culmenus/opus-mt-de-is-finetuned-de-to-is_ancc | [] | null | {
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language: "en"
thumbnail:
tags:
- Spoken language understanding
- speechbrain
- wav2vec2
- hubert
- pytorch
license: "apache-2.0"
datasets:
- SLURP
metrics:
- Accuracy
---
<iframe src="https://ghbtns.com/github-btn.html?user=speechbrain&repo=speechbrain&type=star&count=true&size=large&v=2" frameborder="0" scrollin... | [
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Culmenus/opus-mt-de-is-finetuned-de-to-is_ekkicc | [] | null | {
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"num_beams... | 0 | 2021-11-17T17:49:03Z | ---
language:
- ko
thumbnail:
tags:
- automatic-speech-recognition
- CTC
- Attention
- Conformer
- pytorch
- speechbrain
license: "apache-2.0"
datasets:
- ksponspeech
metrics:
- wer
- cer
---
<iframe src="https://ghbtns.com/github-btn.html?user=speechbrain&repo=speechbrain&type=star&count=true&size=large&v=2" framebor... | [
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language: "de"
thumbnail:
tags:
- automatic-speech-recognition
- CTC
- Attention
- pytorch
- speechbrain
license: "apache-2.0"
datasets:
- common_voice
metrics:
- wer
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---
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CurtisBowser/DialoGPT-medium-sora-three | [] | null | {
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language: "en"
thumbnail:
tags:
- automatic-speech-recognition
- CTC
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- pytorch
- speechbrain
license: "apache-2.0"
datasets:
- librispeech
metrics:
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---
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D3xter1922/distilbert-base-uncased-finetuned-cola | [] | null | {
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language:
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language_bcp47:
- zh-CH
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thumbnail:
tags:
- audio-classification
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D3xter1922/electra-base-discriminator-finetuned-mnli | [] | null | {
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"num_beams... | 0 | 2021-04-27T17:07:22Z | ---
language: "en"
tags:
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license: "apache-2.0"
datasets:
- Voicebank
- DEMAND
metrics:
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---
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DCU-NLP/electra-base-irish-cased-generator-v1 | [
"pytorch",
"electra",
"fill-mask",
"ga",
"transformers",
"irish",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
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"ElectraForMaskedLM"
],
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language: "en"
thumbnail:
tags:
- speechbrain
- Source Separation
- Speech Separation
- Audio Source Separation
- WHAM!
- SepFormer
- Transformer
- audio-to-audio
- audio-source-separation
license: "apache-2.0"
datasets:
- WHAMR!
metrics:
- SI-SNRi
- SDRi
---
<iframe src="https://ghbtns.com/github-btn.html?user=... | [
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DJStomp/TestingSalvoNET | [
"transformers"
] | null | {
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language: en
thumbnail:
tags:
- Spoken language understanding
- speechbrain
license: cc0-1.0
datasets:
- Timers and Such
metrics:
- Accuracy
---
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DKpro000/DialoGPT-medium-harrypotter | [] | null | {
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"num_beams... | 0 | 2021-03-07T16:15:18Z | ---
language: "en"
thumbnail:
tags:
- speechbrain
- embeddings
- Speaker
- Verification
- Identification
- pytorch
- ECAPA
- TDNN
license: "apache-2.0"
datasets:
- voxceleb
metrics:
- EER
widget:
- example_title: VoxCeleb Speaker id10003
src: https://cdn-media.huggingface.co/speech_samples/VoxCeleb1_00003.wav
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DKpro000/DialoGPT-small-harrypotter | [] | null | {
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language: "en"
thumbnail:
tags:
- embeddings
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- pytorch
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- speechbrain
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license: "apache-2.0"
datasets:
- voxceleb
metrics:
- EER
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widget:
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src: https://cdn-media.huggingface.co/speech... | [
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DLNLP/t5-small-finetuned-xsum | [] | null | {
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"num_beams... | 0 | 2021-06-05T02:49:18Z | ---
language: "en"
thumbnail:
tags:
- speechbrain
- embeddings
- Sound
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- pytorch
- ECAPA-TDNN
- TDNN
- Command Recognition
- audio-classification
license: "apache-2.0"
datasets:
- Urbansound8k
metrics:
- Accuracy
---
<iframe src="https://ghbtns.com/github-btn.html?user=speechbrain&repo=s... | [
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DSI/TweetBasedSA | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
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"no_rep... | 29 | null | ---
language: "en"
thumbnail:
tags:
- speechbrain
- VAD
- SAD
- Voice Activity Detection
- Speech Activity Detection
- Speaker Diarization
- pytorch
- CRDNN
- LibriSpeech
- LibryParty
datasets:
- Urbansound8k
metrics:
- Accuracy
---
<iframe src="https://ghbtns.com/github-btn.html?user=speechbrain&repo=speechbrain&typ... | [
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DTAI-KULeuven/mbert-corona-tweets-belgium-curfew-support | [
"pytorch",
"jax",
"bert",
"text-classification",
"multilingual",
"nl",
"fr",
"en",
"arxiv:2104.09947",
"transformers",
"Tweets",
"Sentiment analysis"
] | text-classification | {
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"BertForSequenceClassification"
],
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},
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"no_rep... | 29 | null | # Text classifier using DistilBERT to determine Partisanship
## This is one of many single-class partisanship models
label_0 refers to "left" while label_1 refers to "other".
This model was trained on 40,000 articles.
### Best Practices
This model was optimized for 512 token-length text. Any text below 150 tokens... | [
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