modelId stringlengths 4 112 | sha stringlengths 40 40 | lastModified stringlengths 24 24 | tags list | pipeline_tag stringclasses 29
values | private bool 1
class | author stringlengths 2 38 ⌀ | config null | id stringlengths 4 112 | downloads float64 0 36.8M ⌀ | likes float64 0 712 ⌀ | library_name stringclasses 17
values | __index_level_0__ int64 0 38.5k | readme stringlengths 0 186k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
huggingtweets/thucydiplease | 814c1f43af471868f6840fb17c1e113ee22c2f6f | 2021-05-23T02:15:35.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/thucydiplease | 17 | null | transformers | 9,000 | ---
language: en
thumbnail: https://github.com/borisdayma/huggingtweets/blob/master/img/logo.png?raw=true
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div>
<div style="width: 132px; height:132px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1324921... |
huggingtweets/youronlinedad | 3306b07ac62e97e3c06ed01f6ec02d3b35d7a9b0 | 2021-05-23T05:04:15.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/youronlinedad | 17 | null | transformers | 9,001 | ---
language: en
thumbnail: https://www.huggingtweets.com/youronlinedad/1614100614383/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div>
<div style="width: 132px; height:132px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/11848265809... |
icelab/spacescibert_CR | 5dff26c775e35fe80e50e0d31bb09aff1e5eff95 | 2021-10-25T14:38:27.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | icelab | null | icelab/spacescibert_CR | 17 | null | transformers | 9,002 | ---
widget:
- text: "The CubeSat RF design shall either have one RF inhibit and a RF power output no greater than 1.5W at the transmitter antenna's RF input OR the CubeSat shall have a minimum of two independent RF inhibits (CDS 3.3.9) (ISO 5.5.6)."
---
---
# spacescibert_CR
## Model desciption
This is fine-tuned f... |
indonesian-nlp/wav2vec2-luganda | 67d044bc4b54f96cb75915dcf6cc7bbcf9cfb288 | 2022-01-19T16:19:45.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"lg",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | indonesian-nlp | null | indonesian-nlp/wav2vec2-luganda | 17 | 1 | transformers | 9,003 | ---
language: lg
datasets:
- common_voice
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
license: apache-2.0
model-index:
- name: Wav2Vec2 Luganda by Indonesian-NLP
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice l... |
it5/it5-base-ilgiornale-to-repubblica | db91c86fc720499db2fb99a361076182169d2b96 | 2022-03-09T08:04:46.000Z | [
"pytorch",
"tf",
"jax",
"tensorboard",
"t5",
"text2text-generation",
"it",
"dataset:gsarti/change_it",
"arxiv:2203.03759",
"transformers",
"italian",
"sequence-to-sequence",
"newspaper",
"ilgiornale",
"repubblica",
"style-transfer",
"license:apache-2.0",
"model-index",
"co2_eq_em... | text2text-generation | false | it5 | null | it5/it5-base-ilgiornale-to-repubblica | 17 | null | transformers | 9,004 | ---
language:
- it
license: apache-2.0
datasets:
- gsarti/change_it
tags:
- italian
- sequence-to-sequence
- newspaper
- ilgiornale
- repubblica
- style-transfer
widget:
- text: "WASHINGTON - La Corea del Nord torna dopo nove anni nella blacklist Usa degli Stati considerati sponsor del terrorismo. Come Iran, Siria e Su... |
it5/it5-base-wiki-summarization | d9c0b97204dec4fb765905d1ac50831a8029c557 | 2022-03-09T08:06:40.000Z | [
"pytorch",
"tf",
"jax",
"tensorboard",
"t5",
"text2text-generation",
"it",
"dataset:wits",
"arxiv:2203.03759",
"transformers",
"italian",
"sequence-to-sequence",
"wikipedia",
"summarization",
"wits",
"license:apache-2.0",
"model-index",
"co2_eq_emissions",
"autotrain_compatible"
... | summarization | false | it5 | null | it5/it5-base-wiki-summarization | 17 | null | transformers | 9,005 | ---
language:
- it
license: apache-2.0
datasets:
- wits
tags:
- italian
- sequence-to-sequence
- wikipedia
- summarization
- wits
widget:
- text: "La 5ª Commissione ha competenza per i disegni di legge riguardanti le specifiche materie del bilancio, del personale e dei servizi del Ministero dell'economia, nonché per i ... |
julien-c/EsperBERTo-small-pos | 1183bc1ab394cc09d9c631c07b076cdcedd77954 | 2021-05-20T17:28:42.000Z | [
"pytorch",
"jax",
"roberta",
"token-classification",
"eo",
"transformers",
"autotrain_compatible"
] | token-classification | false | julien-c | null | julien-c/EsperBERTo-small-pos | 17 | 1 | transformers | 9,006 | ---
language: eo
thumbnail: https://huggingface.co/blog/assets/01_how-to-train/EsperBERTo-thumbnail-v2.png
widget:
- text: "Mi estas viro kej estas tago varma."
---
# EsperBERTo: RoBERTa-like Language model trained on Esperanto
**Companion model to blog post https://huggingface.co/blog/how-to-train** 🔥
## Training ... |
juliensimon/autonlp-imdb-demo-hf-16622775 | f679643e1e113864071f50a08815be4652aded48 | 2021-10-11T12:46:02.000Z | [
"pytorch",
"roberta",
"text-classification",
"en",
"dataset:juliensimon/autonlp-data-imdb-demo-hf",
"transformers",
"autonlp"
] | text-classification | false | juliensimon | null | juliensimon/autonlp-imdb-demo-hf-16622775 | 17 | 1 | transformers | 9,007 | ---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
datasets:
- juliensimon/autonlp-data-imdb-demo-hf
---
# Model Trained Using AutoNLP
- Problem type: Binary Classification
- Model ID: 16622775
## Validation Metrics
- Loss: 0.18653589487075806
- Accuracy: 0.9408
- Precision: 0.9537643207855974
- Rec... |
junnyu/roformer_small_discriminator | 411682a5b9cb673344ebd2ebf6482612c1c6006f | 2021-09-22T08:54:23.000Z | [
"pytorch",
"roformer",
"feature-extraction",
"en",
"dataset:openwebtext",
"transformers",
"electra",
"rotary position embedding",
"license:mit"
] | feature-extraction | false | junnyu | null | junnyu/roformer_small_discriminator | 17 | null | transformers | 9,008 | ---
language: en
thumbnail: https://github.com/junnyu
tags:
- pytorch
- electra
- roformer
- rotary position embedding
license: mit
datasets:
- openwebtext
---
# 一、 个人在openwebtext数据集上添加rotary-position-embedding，训练得到的electra-small模型
# 二、 复现结果(dev dataset)
|Model|CoLA|SST|MRPC|STS|QQP|MNLI|QNLI|RTE|Avg.|
|---|---|---|--... |
kaesve/BioBERT_patent_reference_extraction | a1e26ee5926ce7bf00ccc2a08d11d099cf24da91 | 2021-05-19T20:58:49.000Z | [
"pytorch",
"jax",
"bert",
"fill-mask",
"arxiv:2101.01039",
"transformers",
"autotrain_compatible"
] | fill-mask | false | kaesve | null | kaesve/BioBERT_patent_reference_extraction | 17 | null | transformers | 9,009 | # Reference extraction in patents
This repository contains a finetuned BioBERT model that can extract references to scientific literature from patents.
See https://github.com/kaesve/patent-citation-extraction and https://arxiv.org/abs/2101.01039 for more information.
|
kuppuluri/telugu_bertu_ner | c1649a30768be0256c2d4375cc45baf64f1c1199 | 2021-12-02T18:15:04.000Z | [
"pytorch",
"jax",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | kuppuluri | null | kuppuluri/telugu_bertu_ner | 17 | null | transformers | 9,010 | # Named Entity Recognition Model for Telugu
#### How to use
Use the below script from your python terminal as the web interface for inference has few encoding issues for Telugu
PS: If you find my model useful, I would appreciate a note from you as it would encourage me to continue improving it and also add new models... |
ltrctelugu/gpt2_ltrc_telugu | c31edbe619c6cce20bfecaab8b843095c0dd2738 | 2021-05-23T08:35:13.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | ltrctelugu | null | ltrctelugu/gpt2_ltrc_telugu | 17 | null | transformers | 9,011 | Entry not found |
ltrctelugu/ltrc-distilbert | 0fc61ff343b7d8a916b8245293148084c66f25f0 | 2021-11-22T11:34:05.000Z | [
"pytorch",
"distilbert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | ltrctelugu | null | ltrctelugu/ltrc-distilbert | 17 | null | transformers | 9,012 | hello
|
m3hrdadfi/albert-fa-base-v2-ner-peyma | e6f7d8a4e274f0a26de0e2c704c38ad2d7145c73 | 2020-12-26T08:36:20.000Z | [
"pytorch",
"tf",
"albert",
"token-classification",
"fa",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | false | m3hrdadfi | null | m3hrdadfi/albert-fa-base-v2-ner-peyma | 17 | 1 | transformers | 9,013 | ---
language: fa
license: apache-2.0
---
# ALBERT Persian
A Lite BERT for Self-supervised Learning of Language Representations for the Persian Language
> میتونی بهش بگی برت_کوچولو
[ALBERT-Persian](https://github.com/m3hrdadfi/albert-persian) is the first attempt on ALBERT for the Persian Language. The model was tra... |
madlag/bert-base-uncased-squadv1-x2.01-f89.2-d30-hybrid-rewind-opt-v1 | 151170c410fad18bd5890fa53cba8a3c06d56805 | 2021-06-16T15:02:14.000Z | [
"pytorch",
"tf",
"bert",
"question-answering",
"en",
"dataset:squad",
"transformers",
"license:mit",
"autotrain_compatible"
] | question-answering | false | madlag | null | madlag/bert-base-uncased-squadv1-x2.01-f89.2-d30-hybrid-rewind-opt-v1 | 17 | null | transformers | 9,014 | ---
language: en
thumbnail:
license: mit
tags:
- question-answering
-
-
datasets:
- squad
metrics:
- squad
widget:
- text: "Where is the Eiffel Tower located?"
context: "The Eiffel Tower is a wrought-iron lattice tower on the Champ de Mars in Paris, France. It is named after the engineer Gustave Eiffel, whose compa... |
maroo93/squad1.1 | 250b75f3eed58a84c3094d8deb08270287ed5bf2 | 2021-05-19T23:07:37.000Z | [
"pytorch",
"jax",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | maroo93 | null | maroo93/squad1.1 | 17 | null | transformers | 9,015 | Entry not found |
mrm8488/bert-small-finetuned-typo-detection | c78290d7b75061bf5bedab66e589def2cec7372e | 2021-05-25T20:20:35.000Z | [
"pytorch",
"jax",
"bert",
"token-classification",
"en",
"transformers",
"autotrain_compatible"
] | token-classification | false | mrm8488 | null | mrm8488/bert-small-finetuned-typo-detection | 17 | null | transformers | 9,016 | ---
language: en
thumbnail:
widget:
- text: "here there is an error in coment"
---
# BERT SMALL + Typo Detection ✍❌✍✔
[BERT SMALL](https://huggingface.co/google/bert_uncased_L-4_H-512_A-8) fine-tuned on [GitHub Typo Corpus](https://github.com/mhagiwara/github-typo-corpus) for **typo detection** (using *NER* style)
... |
mrm8488/electricidad-base-discriminator | 1353d86e74c5ae322590dcda6e216259b1f72b67 | 2022-03-30T20:42:47.000Z | [
"pytorch",
"electra",
"pretraining",
"es",
"dataset:-large_spanish_corpus",
"transformers",
"Spanish",
"Electra"
] | null | false | mrm8488 | null | mrm8488/electricidad-base-discriminator | 17 | 2 | transformers | 9,017 | ---
language: es
thumbnail: https://i.imgur.com/uxAvBfh.png
tags:
- Spanish
- Electra
datasets:
-large_spanish_corpus
---
## ELECTRICIDAD: The Spanish Electra [Imgur](https://imgur.com/uxAvBfh)
**Electricidad-base-discriminator** (uncased) is a ```base``` Electra like model (discriminator in this case) trained o... |
mrm8488/longformer-base-4096-spanish | 38c75a848ba74f488916841566f57f5ce2c57b60 | 2022-03-30T20:36:36.000Z | [
"pytorch",
"tensorboard",
"roberta",
"fill-mask",
"es",
"dataset:spanish_large_corpus",
"arxiv:2004.05150",
"transformers",
"Long documents",
"longformer",
"bertin",
"spanish",
"license:mit",
"autotrain_compatible"
] | fill-mask | false | mrm8488 | null | mrm8488/longformer-base-4096-spanish | 17 | 7 | transformers | 9,018 | ---
language:
- es
license: mit
widget:
- text: "Manuel Romero ha creado con el equipo de BERTIN un modelo que procesa documentos <mask> largos."
tags:
- Long documents
- longformer
- bertin
- spanish
datasets:
- spanish_large_corpus
---
# longformer-base-4096-spanish
## [Longformer](https://arxiv.org/abs/2004.05150... |
munggok/mt5-large-id-qgen-qa | b2cc736d866cfb585b1096140080532b3ce3cc66 | 2021-01-27T12:55:12.000Z | [
"pytorch",
"t5",
"text2text-generation",
"id",
"dataset:Squad",
"dataset:XQuad",
"dataset:Tydiqa",
"transformers",
"license:mit",
"autotrain_compatible"
] | text2text-generation | false | munggok | null | munggok/mt5-large-id-qgen-qa | 17 | null | transformers | 9,019 | ---
language: "id"
license: "mit"
datasets:
- Squad
- XQuad
- Tydiqa
widget:
- text: "I love you"
---
## Prefix use
Use prefix "question: {question} context: {context}" before input to generate the question answering
e.g
"question: siapa nama saya ? context: nama saya andi. saya tinggal di jakarta. istri saya berna... |
nlpconnect/dpr-nq-reader-roberta-base-v2 | 6e4e658ff4feec24464ee048f89b26b3b8ff4d05 | 2022-01-03T04:35:47.000Z | [
"pytorch",
"roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | nlpconnect | null | nlpconnect/dpr-nq-reader-roberta-base-v2 | 17 | null | transformers | 9,020 | Entry not found |
patrickvonplaten/sew-d-mid-400k-librispeech-clean-100h-ft | 4ae68de4dad4afdcf26b02ea022e528ef7ab4278 | 2021-10-27T23:44:33.000Z | [
"pytorch",
"tensorboard",
"sew-d",
"automatic-speech-recognition",
"transformers",
"librispeech_asr",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | patrickvonplaten | null | patrickvonplaten/sew-d-mid-400k-librispeech-clean-100h-ft | 17 | 1 | transformers | 9,021 | ---
license: apache-2.0
tags:
- automatic-speech-recognition
- librispeech_asr
- generated_from_trainer
model-index:
- name: sew-d-mid-400k-librispeech-clean-100h-ft
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proof... |
patrickvonplaten/wav2vec2-base-timit-fine-tuned | fbe294145f692fa52eccc285e5927b9c7927f8f6 | 2021-10-27T10:49:08.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"dataset:timit_asr",
"transformers",
"timit_asr",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | patrickvonplaten | null | patrickvonplaten/wav2vec2-base-timit-fine-tuned | 17 | null | transformers | 9,022 | ---
license: apache-2.0
tags:
- automatic-speech-recognition
- timit_asr
- generated_from_trainer
datasets:
- timit_asr
model-index:
- name: wav2vec2-base-timit-fine-tuned
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably... |
peterhsu/marian-finetuned-kde4-en-to-zh_TW | 1bb82729445285143405f711752f692a65448848 | 2022-02-28T11:26:43.000Z | [
"pytorch",
"tensorboard",
"marian",
"text2text-generation",
"dataset:kde4",
"transformers",
"translation",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | translation | false | peterhsu | null | peterhsu/marian-finetuned-kde4-en-to-zh_TW | 17 | null | transformers | 9,023 | ---
license: apache-2.0
tags:
- translation
- generated_from_trainer
datasets:
- kde4
metrics:
- bleu
model-index:
- name: marian-finetuned-kde4-en-to-zh_TW
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: kde4
type: kde4
args:... |
philschmid/distilroberta-base-ner-wikiann | 595c043f2d236eda3c67a5fc6ed52f79b3958cf7 | 2022-06-24T11:21:38.000Z | [
"pytorch",
"roberta",
"token-classification",
"dataset:wikiann",
"transformers",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | philschmid | null | philschmid/distilroberta-base-ner-wikiann | 17 | null | transformers | 9,024 | ---
license: apache-2.0
tags:
- token-classification
datasets:
- wikiann
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilroberta-base-ner-wikiann
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: wikiann
type: wikiann
metri... |
ricardo-filho/bert-base-portuguese-cased-finetuned-ner | f79cdaa48bdfd404f576c8f2f1a27ec0e5d99da4 | 2021-11-23T13:48:05.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"dataset:harem",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | token-classification | false | ricardo-filho | null | ricardo-filho/bert-base-portuguese-cased-finetuned-ner | 17 | null | transformers | 9,025 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- harem
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-portuguese-cased-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: harem
type: harem
args... |
sammy786/wav2vec2-xlsr-tatar | c6b788c09ae0d195e8ee66bf2ae119f80470bc71 | 2022-03-23T18:32:40.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"tt",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers",
"generated_from_trainer",
"hf-asr-leaderboard",
"model_for_talk",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | sammy786 | null | sammy786/wav2vec2-xlsr-tatar | 17 | null | transformers | 9,026 | ---
language:
- tt
license: apache-2.0
tags:
- automatic-speech-recognition
- generated_from_trainer
- hf-asr-leaderboard
- model_for_talk
- mozilla-foundation/common_voice_8_0
- robust-speech-event
- tt
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: sammy786/wav2vec2-xlsr-tatar
results:
- tas... |
sebastian-hofstaetter/distilbert-dot-margin_mse-T2-msmarco | f094fd09201e305431b52570d2a9727edf64b394 | 2021-03-16T17:03:58.000Z | [
"pytorch",
"distilbert",
"feature-extraction",
"en",
"dataset:ms_marco",
"arxiv:2010.02666",
"transformers",
"dpr",
"dense-passage-retrieval",
"knowledge-distillation"
] | feature-extraction | false | sebastian-hofstaetter | null | sebastian-hofstaetter/distilbert-dot-margin_mse-T2-msmarco | 17 | 1 | transformers | 9,027 | ---
language: "en"
tags:
- dpr
- dense-passage-retrieval
- knowledge-distillation
datasets:
- ms_marco
---
# Margin-MSE Trained DistilBert for Dense Passage Retrieval
We provide a retrieval trained DistilBert-based model (we call the architecture BERT_Dot). Our model is trained with Margin-MSE using a 3 t... |
seongju/kor-3i4k-bert-base-cased | 12c1152e20a9d293985fa077c90a723bd3257ff4 | 2021-07-20T07:58:11.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | seongju | null | seongju/kor-3i4k-bert-base-cased | 17 | null | transformers | 9,028 | ### Model information
* language : Korean
* fine tuning data : [kor_3i4k](https://huggingface.co/datasets/kor_3i4k)
* License : CC-BY-SA 4.0
* Base model : [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased)
* input : sentence
* output : intent
----
### Train information
* ... |
shamikbose89/mt5-small-finetuned-arxiv-cs-finetuned-arxiv-cs-full | 7a8420078c15eb05d48aa4a5cbb095c09a11779a | 2021-11-19T17:54:25.000Z | [
"pytorch",
"tensorboard",
"mt5",
"text2text-generation",
"transformers",
"generated_from_trainer",
"summarization",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | summarization | false | shamikbose89 | null | shamikbose89/mt5-small-finetuned-arxiv-cs-finetuned-arxiv-cs-full | 17 | 5 | transformers | 9,029 | ---
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... |
shuqi/seed-encoder | f3ca2a12f7ac5921d0d9793ec9e9fb03e6f19aba | 2021-09-18T11:24:50.000Z | [
"pytorch",
"seed_encoder",
"transformers"
] | null | false | shuqi | null | shuqi/seed-encoder | 17 | null | transformers | 9,030 | # 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... |
sismetanin/mbart_ru_sum_gazeta-ru-sentiment-rureviews | 4fedb6d31035d2017f4cb8e2758032035e93ffc1 | 2021-02-25T23:49:57.000Z | [
"pytorch",
"mbart",
"text-classification",
"ru",
"transformers",
"sentiment analysis",
"Russian"
] | text-classification | false | sismetanin | null | sismetanin/mbart_ru_sum_gazeta-ru-sentiment-rureviews | 17 | null | transformers | 9,031 | ---
language:
- ru
tags:
- sentiment analysis
- Russian
---
## MBARTRuSumGazeta-ru-sentiment-RuReviews
MBARTRuSumGazeta-ru-sentiment-RuReviews is a [MBARTRuSumGazeta](https://huggingface.co/IlyaGusev/mbart_ru_sum_gazeta) model fine-tuned on [RuReviews dataset](https://github.com/sismetanin/rureviews) of Russian-lang... |
stanford-crfm/battlestar-gpt2-small-x49 | 2f4e2079c9ac92c2b5c6fecc19fae645bcef56fa | 2022-06-20T09:04:32.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | stanford-crfm | null | stanford-crfm/battlestar-gpt2-small-x49 | 17 | null | transformers | 9,032 | Entry not found |
subbareddyiiit/TeElectra | 5ec4c5d8a5fa681713005efc391e26e05726f0e6 | 2020-06-21T06:59:39.000Z | [
"pytorch",
"electra",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | subbareddyiiit | null | subbareddyiiit/TeElectra | 17 | null | transformers | 9,033 | Entry not found |
tals/albert-base-vitaminc_flagging | 1e5f38d76c4d9402bf0c7d73e1aab6eaafca0ea8 | 2022-06-22T23:56:43.000Z | [
"pytorch",
"albert",
"text-classification",
"python",
"dataset:fever",
"dataset:glue",
"dataset:tals/vitaminc",
"transformers"
] | text-classification | false | tals | null | tals/albert-base-vitaminc_flagging | 17 | null | transformers | 9,034 | ---
language: python
datasets:
- fever
- glue
- tals/vitaminc
---
# Details
Model used in [Get Your Vitamin C! Robust Fact Verification with Contrastive Evidence](https://aclanthology.org/2021.naacl-main.52/) (Schuster et al., NAACL 21`).
For more details see: https://github.com/TalSchuster/VitaminC
When using this m... |
trnt/twitter_emotions | 0fdc42320272eddfe43aa03670ac20c5028a7e9a | 2021-11-20T04:31:53.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | trnt | null | trnt/twitter_emotions | 17 | 1 | transformers | 9,035 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
model-index:
- name: twitter_emotions
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: default
metrics:
- name: Accu... |
turtlesoupy/inverse-dictionary-model-v1 | 485568f794dce00946739bf86e31841623655087 | 2021-05-23T13:17:21.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | turtlesoupy | null | turtlesoupy/inverse-dictionary-model-v1 | 17 | null | transformers | 9,036 | Entry not found |
yhavinga/gpt-neo-1.3B-dutch | 02db444ac45c0ed6dfebf10010eeab7fb3a1a0ae | 2022-03-20T10:20:34.000Z | [
"pytorch",
"jax",
"tensorboard",
"gpt_neo",
"text-generation",
"nl",
"dataset:yhavinga/mc4_nl_cleaned",
"transformers",
"gpt-neo-1.3B",
"gpt-neo"
] | text-generation | false | yhavinga | null | yhavinga/gpt-neo-1.3B-dutch | 17 | null | transformers | 9,037 | ---
language: nl
widget:
- text: "In het jaar 2030 zullen we"
- text: "Toen ik gisteren volledig in de ban was van"
- text: "Studenten en leraren van de Bogazici Universiteit in de Turkse stad Istanbul"
- text: "In Israël was een strenge lockdown"
tags:
- gpt-neo-1.3B
- gpt-neo
pipeline_tag: text-generation
datasets:
-... |
bookbot/distil-wav2vec2-adult-child-cls-37m | 80548f793c175d52787f726302db721c6fd25bf8 | 2022-02-26T14:49:52.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"audio-classification",
"en",
"arxiv:2006.11477",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | audio-classification | false | bookbot | null | bookbot/distil-wav2vec2-adult-child-cls-37m | 17 | null | transformers | 9,038 | ---
language: en
license: apache-2.0
tags:
- audio-classification
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distil-wav2vec2-adult-child-cls-37m
results: []
---
# DistilWav2Vec2 Adult/Child Speech Classifier 37M
DistilWav2Vec2 Adult/Child Speech Classifier is an audio classif... |
abdusahmbzuai/arabert-ner | d0903445372670c4402f3441ac3723c9dcfc5bc0 | 2022-03-01T15:53:14.000Z | [
"pytorch",
"bert",
"token-classification",
"ar",
"dataset:wikiann",
"transformers",
"ner",
"classification",
"autotrain_compatible"
] | token-classification | false | abdusahmbzuai | null | abdusahmbzuai/arabert-ner | 17 | 1 | transformers | 9,039 |
---
pipeline_tag: token-classification
language: ar
datasets:
- wikiann
task_ids:
- named-entity-recognition
tags:
- "ner"
- "ar"
- "classification"
widget:
- text: "كريستيانو رونالدو يلعب مع نادي يوفنتوس"
example_title: "Sentence 1"
- text: "تخرج أحمد من الجامعة الأمريكية في الشارقة الشهر الماضي"
example_title:... |
davanstrien/convnext_flyswot | ba93cdfc85a8cc69f491717f7f184a03cbca78d8 | 2022-03-01T20:47:35.000Z | [
"pytorch",
"convnext",
"image-classification",
"dataset:image_folder",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | image-classification | false | davanstrien | null | davanstrien/convnext_flyswot | 17 | null | transformers | 9,040 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- f1
model-index:
- name: convnext_flyswot
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: image_folder
type: image_folder
args: default
metrics:
-... |
davanstrien/flyswot_iiif | d8b0a089e42854c5c5f5129ecfc83a8285d45670 | 2022-03-02T07:59:30.000Z | [
"pytorch",
"convnext",
"image-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | image-classification | false | davanstrien | null | davanstrien/flyswot_iiif | 17 | null | transformers | 9,041 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: flyswot_iiif
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. -->
# flyswot_... |
Ameer05/bart-large-cnn-samsum-rescom-finetuned-resume-summarizer-10-epoch-tweak-lr-8-100-1 | c0b4d0d486b0ffe8c8cf79ecf7001bb7a2090794 | 2022-03-08T16:43:01.000Z | [
"pytorch",
"tensorboard",
"bart",
"text2text-generation",
"transformers",
"summarization",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | summarization | false | Ameer05 | null | Ameer05/bart-large-cnn-samsum-rescom-finetuned-resume-summarizer-10-epoch-tweak-lr-8-100-1 | 17 | null | transformers | 9,042 | ---
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-large-cnn-samsum-rescom-finetuned-resume-summarizer-10-epoch-tweak-lr-8-100-1
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably... |
AlekseyKorshuk/bert-finetuned-ner | 58198745f8dd6219a7303702eaa3596570465bab | 2022-03-08T14:27:56.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"dataset:wnut_17",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | AlekseyKorshuk | null | AlekseyKorshuk/bert-finetuned-ner | 17 | null | transformers | 9,043 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wnut_17
model-index:
- name: bert-finetuned-ner
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->... |
AmrSheta/Meme | ab6b8aaabee48905907041dc1595f954d9e17b02 | 2022-03-12T20:50:10.000Z | [
"pytorch",
"bert",
"feature-extraction",
"transformers",
"text-classification"
] | text-classification | false | AmrSheta | null | AmrSheta/Meme | 17 | null | transformers | 9,044 | ---
tags:
- text-classification
---
#meme description classification |
facebook/m2m100-12B-avg-5-ckpt | a8f832018c8e51e3db1652e7ae9652664a1e4647 | 2022-05-26T22:26:32.000Z | [
"pytorch",
"m2m_100",
"text2text-generation",
"multilingual",
"af",
"am",
"ar",
"ast",
"az",
"ba",
"be",
"bg",
"bn",
"br",
"bs",
"ca",
"ceb",
"cs",
"cy",
"da",
"de",
"el",
"en",
"es",
"et",
"fa",
"ff",
"fi",
"fr",
"fy",
"ga",
"gd",
"gl",
"gu",
"ha"... | text2text-generation | false | facebook | null | facebook/m2m100-12B-avg-5-ckpt | 17 | null | transformers | 9,045 | ---
language:
- multilingual
- af
- am
- ar
- ast
- az
- ba
- be
- bg
- bn
- br
- bs
- ca
- ceb
- cs
- cy
- da
- de
- el
- en
- es
- et
- fa
- ff
- fi
- fr
- fy
- ga
- gd
- gl
- gu
- ha
- he
- hi
- hr
- ht
- hu
- hy
- id
- ig
- ilo
- is
- it
- ja
- jv
- ka
- kk
- km
- kn
- ko
- lb
- lg
- ln
- lo
- lt
- lv
- mg
- mk
- ... |
saattrupdan/job-listing-relevance-model | 3751de206442b9b400d6660d7da787a74aba09c2 | 2022-03-22T19:51:07.000Z | [
"pytorch",
"xlm-roberta",
"text-classification",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index"
] | text-classification | false | saattrupdan | null | saattrupdan/job-listing-relevance-model | 17 | null | transformers | 9,046 | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: job-listing-relevance-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. -->
# job-listing-re... |
RomanEnikeev/distilbert-base-uncased-finetuned-cola | f8049e8669ceb20d8a2282e612b3229840074d7a | 2022-03-25T09:13:46.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:glue",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | RomanEnikeev | null | RomanEnikeev/distilbert-base-uncased-finetuned-cola | 17 | 0 | transformers | 9,047 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: distilbert-base-uncased-finetuned-cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: cola
met... |
l3cube-pune/hing-mbert-mixed | 865aa54a29dbb68d074172807e17dda68dc7ecde | 2022-06-26T15:12:05.000Z | [
"pytorch",
"bert",
"fill-mask",
"hi",
"en",
"dataset:L3Cube-HingCorpus",
"arxiv:2204.08398",
"transformers",
"codemix",
"license:cc-by-4.0",
"autotrain_compatible"
] | fill-mask | false | l3cube-pune | null | l3cube-pune/hing-mbert-mixed | 17 | null | transformers | 9,048 | ---
license: cc-by-4.0
language:
- hi
- en
tags:
- hi
- en
- codemix
datasets:
- L3Cube-HingCorpus
---
## HingBERT-Mixed
HingBERT-Mixed is a Hindi-English code-mixed BERT model trained on roman + devanagari text. It is a base BERT model fine-tuned on mixed script L3Cube-HingCorpus.
<br>
[dataset link] (https://github... |
Graphcore/lxmert-gqa-uncased | 7827f5b7093dd9ef2119df8ab3a512526cdffe68 | 2022-05-25T18:28:12.000Z | [
"pytorch",
"lxmert",
"question-answering",
"dataset:Graphcore/gqa-lxmert",
"arxiv:1908.07490",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | question-answering | false | Graphcore | null | Graphcore/lxmert-gqa-uncased | 17 | null | transformers | 9,049 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- Graphcore/gqa-lxmert
metrics:
- accuracy
model-index:
- name: gqa
results:
- task:
name: Question Answering
type: question-answering
dataset:
name: Graphcore/gqa-lxmert
type: Graphcore/gqa-lxmert
args: gqa
metri... |
IIC/roberta-base-bne-ranker | 8ee5133c03047e93559dfbfd6f2122045e91e8c3 | 2022-04-02T15:04:54.000Z | [
"pytorch",
"roberta",
"text-classification",
"es",
"dataset:IIC/msmarco_es",
"transformers",
"sentence similarity",
"passage reranking",
"model-index"
] | text-classification | false | IIC | null | IIC/roberta-base-bne-ranker | 17 | null | transformers | 9,050 | ---
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... |
Meowren/MichaelScottBott | d48033535b3d403e3a55b76c3323f38588441195 | 2022-05-16T16:03:13.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | Meowren | null | Meowren/MichaelScottBott | 17 | null | transformers | 9,051 | ---
tags:
- conversational
---
# Michael Scott DialoGPT Model
|
nielsr/convnext-tiny-finetuned-eurostat | f836aee3c8bc4e7424702ed00d2b8343bd0dbf21 | 2022-04-04T19:25:58.000Z | [
"pytorch",
"convnext",
"image-classification",
"dataset:eurosat",
"transformers",
"license:apache-2.0"
] | image-classification | false | nielsr | null | nielsr/convnext-tiny-finetuned-eurostat | 17 | null | transformers | 9,052 | ---
license: apache-2.0
datasets:
- eurosat
widget:
- src: forest.png
example_title: Forest
---
# ConvNext fine-tuned on Eurosat
This model is a `facebook/convnext-tiny-224` model fine-tuned on the [Eurosat dataset](https://github.com/phelber/EuroSAT). |
Intel/bert-base-uncased-mrpc-int8-qat | 54b72a05d03d7085c951b861c3d546cfe5de354a | 2022-06-10T02:43:22.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"dataset:mrpc",
"transformers",
"text-classfication",
"int8",
"Intel® Neural Compressor",
"QuantizationAwareTraining",
"license:apache-2.0"
] | text-classification | false | Intel | null | Intel/bert-base-uncased-mrpc-int8-qat | 17 | null | transformers | 9,053 | ---
language: en
license: apache-2.0
tags:
- text-classfication
- int8
- Intel® Neural Compressor
- QuantizationAwareTraining
datasets:
- mrpc
metrics:
- f1
---
# INT8 BERT base uncased finetuned MRPC
### QuantizationAwareTraining
This is an INT8 PyTorch model quantized with [Intel® Neural Compressor](https://gith... |
Stremie/bert-base-uncased-clickbait-keywords | a629da66d459d9ced721b258d5f5ca5f5cad1db1 | 2022-04-18T12:49:08.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | Stremie | null | Stremie/bert-base-uncased-clickbait-keywords | 17 | null | transformers | 9,054 | This model classifies whether a tweet is clickbait or not. It has been trained using [Webis-Clickbait-17](https://webis.de/data/webis-clickbait-17.html) dataset. Input is composed of 'postText' + '[SEP]' + 'targetKeywords'. Achieved ~0.7 F1-score on test data. |
Kuray107/librispeech-100h-supervised-meta | 263762b247ca3d1590e5d0f257fac9ea3b7bb836 | 2022-04-11T14:24:58.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | Kuray107 | null | Kuray107/librispeech-100h-supervised-meta | 17 | null | transformers | 9,055 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: librispeech-100h-supervised-meta
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. -->
# li... |
Conrad747/lg-en | 49f97fb3cc1b52693783027c6a3d44f14288d83e | 2022-07-20T13:39:31.000Z | [
"pytorch",
"tensorboard",
"marian",
"text2text-generation",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | Conrad747 | null | Conrad747/lg-en | 17 | null | transformers | 9,056 | ---
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: lg-en
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. -->
# lg-en
This model is a fine-tuned... |
amir36/distilbert-base-uncased-finetuned-emotion | d721f69df9829e53438617352c3f33e8e6313068 | 2022-07-14T02:52:28.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | amir36 | null | amir36/distilbert-base-uncased-finetuned-emotion | 17 | null | transformers | 9,057 | ---
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... |
studio-ousia/luke-large-lite | 367bdf0609d247be6ce1eb76f9f228d40d26d05a | 2022-04-13T10:32:20.000Z | [
"pytorch",
"luke",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | studio-ousia | null | studio-ousia/luke-large-lite | 17 | null | transformers | 9,058 | Entry not found |
Toshifumi/distilbert-base-multilingual-cased-finetuned-emotion | c44daf307230625367378c08e353508ae3f29a16 | 2022-04-13T12:30:50.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | Toshifumi | null | Toshifumi/distilbert-base-multilingual-cased-finetuned-emotion | 17 | null | transformers | 9,059 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-multilingual-cased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
ar... |
rmihaylov/bert-base-pos-theseus-bg | e85ab91f3bc5524d7e491d17883feb065203b2f8 | 2022-04-16T19:26:17.000Z | [
"pytorch",
"bert",
"token-classification",
"bg",
"dataset:oscar",
"dataset:chitanka",
"dataset:wikipedia",
"arxiv:1810.04805",
"arxiv:2002.02925",
"transformers",
"torch",
"license:mit",
"autotrain_compatible"
] | token-classification | false | rmihaylov | null | rmihaylov/bert-base-pos-theseus-bg | 17 | null | transformers | 9,060 | ---
inference: false
language:
- bg
license: mit
datasets:
- oscar
- chitanka
- wikipedia
tags:
- torch
---
# BERT BASE (cased) finetuned on Bulgarian part-of-speech data
Pretrained model on Bulgarian language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/18... |
ToToKr/kobigbird-bert-base-finetuned-klue | 518fbcf145fdcc835d00a37a895bd7b0282b1cf5 | 2022-06-07T08:24:06.000Z | [
"pytorch",
"tensorboard",
"big_bird",
"question-answering",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | question-answering | false | ToToKr | null | ToToKr/kobigbird-bert-base-finetuned-klue | 17 | null | transformers | 9,061 | ---
tags:
- generated_from_trainer
model-index:
- name: kobigbird-bert-base-finetuned-klue
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. -->
# kobigbird-bert-base-... |
AJGP/bert-finetuned-ner | d7b33d9a94cbae6b6a6c910649e7bd30ccebd4ec | 2022-04-17T14:57:27.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"dataset:conll2003",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | AJGP | null | AJGP/bert-finetuned-ner | 17 | null | transformers | 9,062 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type: conll2003
args: c... |
mwong/albert-base-fever-claim-related | 4848442a348fedbb771c97df962650c0644884c4 | 2022-06-24T03:34:53.000Z | [
"pytorch",
"albert",
"text-classification",
"en",
"dataset:mwong/fever-claim-related",
"transformers",
"text classification",
"fact checking",
"license:mit"
] | text-classification | false | mwong | null | mwong/albert-base-fever-claim-related | 17 | 1 | transformers | 9,063 | ---
language: en
license: mit
tags:
- text classification
- fact checking
datasets:
- mwong/fever-claim-related
widget:
- text: "Earth’s changing climate is a critical issue and poses the risk of significant environmental, social and economic disruptions around the globe.</s></s>Because of fears of climate change and a... |
Intel/bert-base-uncased-mrpc-int8-dynamic | eab02b076b47301343cb77fa7cf23d029bee7376 | 2022-06-10T02:32:38.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"dataset:mrpc",
"transformers",
"text-classfication",
"int8",
"Intel® Neural Compressor",
"PostTrainingDynamic",
"license:apache-2.0"
] | text-classification | false | Intel | null | Intel/bert-base-uncased-mrpc-int8-dynamic | 17 | null | transformers | 9,064 | ---
language: en
license: apache-2.0
tags:
- text-classfication
- int8
- Intel® Neural Compressor
- PostTrainingDynamic
datasets:
- mrpc
metrics:
- f1
---
# INT8 BERT base uncased finetuned MRPC
### Post-training dynamic quantization
This is an INT8 PyTorch model quantized with [Intel® Neural Compressor](https://g... |
Hate-speech-CNERG/tamil-codemixed-abusive-MuRIL | 6eef32cd2cd8eb9f26dd76beaeec370ab6c48b2f | 2022-05-03T08:52:47.000Z | [
"pytorch",
"bert",
"text-classification",
"ta-en",
"arxiv:2204.12543",
"transformers",
"license:afl-3.0"
] | text-classification | false | Hate-speech-CNERG | null | Hate-speech-CNERG/tamil-codemixed-abusive-MuRIL | 17 | null | transformers | 9,065 | ---
language: ta-en
license: afl-3.0
---
This model is used to detect **abusive speech** in **Code-Mixed Tamil**. It is finetuned on MuRIL model using Code-Mixed Tamil abusive speech dataset.
The model is trained with learning rates of 2e-5. Training code can be found at this [url](https://github.com/hate-alert/IndicA... |
benjamin/gpt2-wechsel-ukrainian | b654dd26f575dc9d2ff07bf501e5c442b22d5e39 | 2022-04-29T17:42:44.000Z | [
"pytorch",
"gpt2",
"text-generation",
"uk",
"arxiv:2112.06598",
"transformers",
"license:mit"
] | text-generation | false | benjamin | null | benjamin/gpt2-wechsel-ukrainian | 17 | 1 | transformers | 9,066 | ---
license: mit
language: uk
---
# gpt2-wechsel-ukrainian
[`gpt2`](https://huggingface.co/gpt2) transferred to Ukrainian using the method from the NAACL2022 paper [WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models](https://arxiv.org/abs/2112.065989). |
KoenBronstring/finetuning-sentiment-model-3000-samples | ae2500fe723ee0c8ac6856d16e7815bbfda2e57e | 2022-05-04T17:53:58.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:imdb",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | KoenBronstring | null | KoenBronstring/finetuning-sentiment-model-3000-samples | 17 | null | transformers | 9,067 | ---
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... |
mikeadimech/pegasus-qmsum-meeting-summarization | 1c8b4f4ac589d791c6f976cce4d05e945ee84cb9 | 2022-05-25T16:15:41.000Z | [
"pytorch",
"pegasus",
"text2text-generation",
"dataset:yawnick/QMSum",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | mikeadimech | null | mikeadimech/pegasus-qmsum-meeting-summarization | 17 | null | transformers | 9,068 | ---
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: pegasus-qmsum-meeting-summarization
results: []
datasets:
- yawnick/QMSum
---
<!-- 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... |
pietrolesci/bert-base-uncased-mnli | df493f6a1838576b54552afcee3a08dabb7579b2 | 2022-05-03T10:10:29.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | pietrolesci | null | pietrolesci/bert-base-uncased-mnli | 17 | null | transformers | 9,069 | Entry not found |
arxyzan/data2vec-roberta-base | 68434a0eeab8ff055b5ca13aa7e9a972233948aa | 2022-05-17T06:05:15.000Z | [
"pytorch",
"roberta",
"feature-extraction",
"arxiv:2202.03555",
"transformers"
] | feature-extraction | false | arxyzan | null | arxyzan/data2vec-roberta-base | 17 | null | transformers | 9,070 | A RoBERTa model trained using Data2Vec based on the paper [data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language](https://arxiv.org/abs/2202.03555).<br>
This model is provided here for [this repo](https://github.com/AryanShekarlaban/data2vec-pytorch) but was NOT trained using that co... |
TweebankNLP/bertweet-tb2-ner | 773f0129e5bb057190d69e79068f23391f0deb7b | 2022-05-05T00:23:29.000Z | [
"pytorch",
"roberta",
"token-classification",
"arxiv:2201.07281",
"transformers",
"license:cc-by-nc-4.0",
"autotrain_compatible"
] | token-classification | false | TweebankNLP | null | TweebankNLP/bertweet-tb2-ner | 17 | null | transformers | 9,071 | ---
license: cc-by-nc-4.0
---
## Model Specification
- This is one **baseline Twitter NER model (with 73.71\% Entity-Level F1)** on Tweebank V2's NER benchmark (also called `Tweebank-NER`), trained on the Tweebank-NER training data.
- **If you are looking for the SOTA Twitter NER model**, please go to this [HuggingFa... |
Wakaka/bert-finetuned-imdb | 000f4675fd6b9dab2afadd4b79f35cfa9d56698f | 2022-05-06T06:38:19.000Z | [
"pytorch",
"bert",
"text-classification",
"dataset:imdb",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | Wakaka | null | Wakaka/bert-finetuned-imdb | 17 | null | transformers | 9,072 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: bert-finetuned-imdb
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
args: plain_text
metrics:
- name: Accurac... |
eslamxm/mt5-base-finetuned-persian-finetuned-persian-arabic | 6213dea489fa88fa70afd5f55e8dce9e24495cb3 | 2022-05-09T05:50:11.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"dataset:xlsum",
"transformers",
"summarization",
"arabic",
"ar",
"Abstractive Summarization",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | summarization | false | eslamxm | null | eslamxm/mt5-base-finetuned-persian-finetuned-persian-arabic | 17 | null | transformers | 9,073 | ---
license: apache-2.0
tags:
- summarization
- arabic
- ar
- mt5
- Abstractive Summarization
- generated_from_trainer
datasets:
- xlsum
model-index:
- name: mt5-base-finetuned-persian-finetuned-persian-arabic
results: []
---
<!-- This model card has been generated automatically according to the information the Trai... |
CEBaB/lstm.CEBaB.sa.5-class.exclusive.seed_42 | 81da16c37a9842d084e09fb98ce0eed9dd6e7174 | 2022-05-10T23:55:29.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | CEBaB | null | CEBaB/lstm.CEBaB.sa.5-class.exclusive.seed_42 | 17 | null | transformers | 9,074 | Entry not found |
CEBaB/lstm.CEBaB.sa.2-class.exclusive.seed_66 | 5926cb9615a5167fa024aa89e16c63763449e14d | 2022-05-11T00:12:47.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | CEBaB | null | CEBaB/lstm.CEBaB.sa.2-class.exclusive.seed_66 | 17 | null | transformers | 9,075 | Entry not found |
CEBaB/lstm.CEBaB.sa.3-class.exclusive.seed_66 | 203d0253d4d65b3e5f2fc468b9a3625af2092f3d | 2022-05-11T00:29:46.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | CEBaB | null | CEBaB/lstm.CEBaB.sa.3-class.exclusive.seed_66 | 17 | null | transformers | 9,076 | Entry not found |
CEBaB/lstm.CEBaB.sa.5-class.exclusive.seed_66 | 1f5d7fbecaa02c186081dc39a5f02fc44b6e92c6 | 2022-05-11T00:47:25.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | CEBaB | null | CEBaB/lstm.CEBaB.sa.5-class.exclusive.seed_66 | 17 | null | transformers | 9,077 | Entry not found |
CEBaB/lstm.CEBaB.sa.2-class.exclusive.seed_77 | 1bc9ad59b02f79207afed09a393b17cb63817eb3 | 2022-05-11T01:04:38.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | CEBaB | null | CEBaB/lstm.CEBaB.sa.2-class.exclusive.seed_77 | 17 | null | transformers | 9,078 | Entry not found |
CEBaB/lstm.CEBaB.sa.2-class.exclusive.seed_88 | 04dd7f7b2caa39f8c07dabf9d240decec4d9521e | 2022-05-11T01:57:06.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | CEBaB | null | CEBaB/lstm.CEBaB.sa.2-class.exclusive.seed_88 | 17 | null | transformers | 9,079 | Entry not found |
CEBaB/lstm.CEBaB.sa.3-class.exclusive.seed_88 | 2c35cae91b5a0f6ea6c6f18e04b5397966a8c69f | 2022-05-11T02:14:28.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | CEBaB | null | CEBaB/lstm.CEBaB.sa.3-class.exclusive.seed_88 | 17 | null | transformers | 9,080 | Entry not found |
CEBaB/lstm.CEBaB.sa.5-class.exclusive.seed_88 | 771f8dc662e5bb81aa34310c453e61b39396b90a | 2022-05-11T02:31:28.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | CEBaB | null | CEBaB/lstm.CEBaB.sa.5-class.exclusive.seed_88 | 17 | null | transformers | 9,081 | Entry not found |
CEBaB/lstm.CEBaB.sa.2-class.exclusive.seed_99 | 26c4fa8bb1925a918a48c637e3f9c0e869da4651 | 2022-05-11T02:48:32.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | CEBaB | null | CEBaB/lstm.CEBaB.sa.2-class.exclusive.seed_99 | 17 | null | transformers | 9,082 | Entry not found |
CEBaB/lstm.CEBaB.sa.3-class.exclusive.seed_99 | 4bfb3006a776db8aa19b5846581aeabab64a65f9 | 2022-05-11T03:05:48.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | CEBaB | null | CEBaB/lstm.CEBaB.sa.3-class.exclusive.seed_99 | 17 | null | transformers | 9,083 | Entry not found |
CEBaB/lstm.CEBaB.sa.5-class.exclusive.seed_99 | 057ec2347ae97c6eb4562e75b70da01a0250b1e8 | 2022-05-11T03:22:57.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | CEBaB | null | CEBaB/lstm.CEBaB.sa.5-class.exclusive.seed_99 | 17 | null | transformers | 9,084 | Entry not found |
SalamaThanks/SalamaThanksTransformer_fil2en_v2 | ed75269aa77cac1ada651a21f8c2777235a65090 | 2022-05-11T05:57:37.000Z | [
"pytorch",
"marian",
"text2text-generation",
"transformers",
"license:afl-3.0",
"autotrain_compatible"
] | text2text-generation | false | SalamaThanks | null | SalamaThanks/SalamaThanksTransformer_fil2en_v2 | 17 | null | transformers | 9,085 | ---
license: afl-3.0
---
SalamaThanks Transformer for Filipino-to-English Text Translation version 2.
A finetuned model based on the Helsinki-NLP/opus-mt-en-tl transformer model. |
Paleontolog/bert_sentence_classifier | 7a617b1f1dffb0f487af6a89fa92f2fed7ad7369 | 2022-05-11T14:05:26.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | Paleontolog | null | Paleontolog/bert_sentence_classifier | 17 | null | transformers | 9,086 | Entry not found |
enoriega/kw_pubmed_5000_0.00006 | 7589c51c64d9b77b1dadf3b8d821190f4fcf92a9 | 2022-05-12T11:09:45.000Z | [
"pytorch",
"tensorboard",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | enoriega | null | enoriega/kw_pubmed_5000_0.00006 | 17 | null | transformers | 9,087 | Entry not found |
nikitast/lang-classifier-roberta | 33ed588b1fb6089c6e43c57917e067f4e3cebc11 | 2022-07-18T11:19:10.000Z | [
"pytorch",
"xlm-roberta",
"text-classification",
"ru",
"uk",
"be",
"kk",
"az",
"hy",
"ka",
"he",
"en",
"de",
"dataset:open_subtitles",
"dataset:tatoeba",
"dataset:oscar",
"transformers",
"language classification"
] | text-classification | false | nikitast | null | nikitast/lang-classifier-roberta | 17 | 1 | transformers | 9,088 | ---
language:
- ru
- uk
- be
- kk
- az
- hy
- ka
- he
- en
- de
tags:
- language classification
datasets:
- open_subtitles
- tatoeba
- oscar
---
# RoBERTa for Single Language Classification
## Training
RoBERTa fine-tuned on small parts of Open Subtitles, Oscar and Tatoeba datasets (~9k samples per language).
| data ... |
Bryan0123/bert-hashtag-to-hashtag-20 | eb089721e6a7585e6a5fe7a41474c9fd426157cf | 2022-05-15T05:02:12.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | Bryan0123 | null | Bryan0123/bert-hashtag-to-hashtag-20 | 17 | null | transformers | 9,089 | Entry not found |
vives/distilbert-base-uncased-finetuned-cvent-2022 | de2d5128d93fe20949d25eb1ce7351ea78e0a489 | 2022-05-13T20:37:30.000Z | [
"pytorch",
"distilbert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | vives | null | vives/distilbert-base-uncased-finetuned-cvent-2022 | 17 | null | transformers | 9,090 | Entry not found |
dipstheman/DialoGPT-small-humanconversation | aa81c831d8303afbaf1522ce24f7f569185f3ce2 | 2022-05-16T22:05:07.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | dipstheman | null | dipstheman/DialoGPT-small-humanconversation | 17 | null | transformers | 9,091 | ---
tags:
- conversational
---
#human conversation DialoGPT Model |
SyedMujtabaHassanRizvi/convnext-tiny-finetuned-eurosat | cb9800974779afb36ab23ed01f92b41e77752d4e | 2022-05-19T12:48:40.000Z | [
"pytorch",
"convnext",
"image-classification",
"transformers"
] | image-classification | false | SyedMujtabaHassanRizvi | null | SyedMujtabaHassanRizvi/convnext-tiny-finetuned-eurosat | 17 | null | transformers | 9,092 | Entry not found |
animalthemuppet/bert-finetuned-ner | c5082885310360f718e076f7d05b9c19e5cf7e73 | 2022-05-22T17:04:06.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"dataset:conll2003",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | animalthemuppet | null | animalthemuppet/bert-finetuned-ner | 17 | null | transformers | 9,093 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type: conll2003
args: c... |
eslamxm/mt5-base-finetuned-ar-sp | 0ff443165c15491cae6b60db5ca9cca22bdf693e | 2022-05-23T23:27:43.000Z | [
"pytorch",
"tensorboard",
"mt5",
"text2text-generation",
"transformers",
"summarization",
"arabic",
"am",
"es",
"amharic",
"Abstractive Summarization",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | summarization | false | eslamxm | null | eslamxm/mt5-base-finetuned-ar-sp | 17 | null | transformers | 9,094 | ---
license: apache-2.0
tags:
- summarization
- arabic
- am
- es
- amharic
- mt5
- Abstractive Summarization
- generated_from_trainer
model-index:
- name: mt5-base-finetuned-ar-sp
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should ... |
hd94/roberta-hindi | 10c6f839598e6f2acc27ff67627d89ceb2e8dbda | 2022-05-24T09:42:28.000Z | [
"pytorch",
"xlm-roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | hd94 | null | hd94/roberta-hindi | 17 | null | transformers | 9,095 | Entry not found |
Ravindra001/bert-finetuned-ner | 2967d6f51750d99db081eea1a9e5bf703c3bf439 | 2022-07-28T09:29:11.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"dataset:wikiann",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | Ravindra001 | null | Ravindra001/bert-finetuned-ner | 17 | null | transformers | 9,096 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wikiann
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: wikiann
type: wikiann
args: en
... |
Mathking/all-mpnet-base-v2_outcome_sim | af3847ab3ef6e74ac548712a0fe6a88a115b3485 | 2022-05-25T13:40:22.000Z | [
"pytorch",
"mpnet",
"feature-extraction",
"sentence-transformers",
"sentence-similarity"
] | sentence-similarity | false | Mathking | null | Mathking/all-mpnet-base-v2_outcome_sim | 17 | null | sentence-transformers | 9,097 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
---
# {MODEL_NAME}
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic... |
aditya2029/gpt-neo-genre-storygenerator | d63e6a511a2eab462b397d813f07ab6e79ec807c | 2022-05-26T02:27:55.000Z | [
"pytorch",
"gpt_neo",
"text-generation",
"transformers"
] | text-generation | false | aditya2029 | null | aditya2029/gpt-neo-genre-storygenerator | 17 | null | transformers | 9,098 | |
andidu/paraphrase-ru | 05678a1fae2802efc7ba76715569b3043a001b9a | 2022-05-28T07:05:58.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | andidu | null | andidu/paraphrase-ru | 17 | null | transformers | 9,099 | Entry not found |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.