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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
hsaglamlar/stress_twitter | 6666c77ad4c4a707c9f1891ddd66b78dbd083464 | 2022-07-25T20:55:40.000Z | [
"pytorch",
"roberta",
"text-classification",
"en",
"dataset:hsaglamlar/autotrain-data-stress_v2",
"transformers",
"autotrain",
"co2_eq_emissions"
] | text-classification | false | hsaglamlar | null | hsaglamlar/stress_twitter | 29 | null | transformers | 7,300 | ---
tags: autotrain
language: en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- hsaglamlar/autotrain-data-stress_v2
co2_eq_emissions: 2.7282806494855265
---
# Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 1178743973
- CO2 Emissions (in grams): 2.7282806494855265
## Validation Met... |
BossLee/t5-gec | ee42828b55034da69a844b558cf4586249e9c0e2 | 2021-11-11T11:42:45.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | BossLee | null | BossLee/t5-gec | 28 | null | transformers | 7,301 | Entry not found |
BrianTin/MTBERT | cf1b9576c65e8625e10fe2901088f9ffc57645b8 | 2021-05-18T17:08:50.000Z | [
"pytorch",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | BrianTin | null | BrianTin/MTBERT | 28 | null | transformers | 7,302 | Entry not found |
CoderEFE/DialoGPT-marxbot | 4e12cbe19700342269fa60b995b72c6b0f88a7ab | 2021-06-07T01:24:25.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | CoderEFE | null | CoderEFE/DialoGPT-marxbot | 28 | null | transformers | 7,303 | ---
tags:
- conversational
---
Chat with the model:
```python
from transformers import AutoTokenizer, AutoModelWithLMHead
tokenizer = AutoTokenizer.from_pretrained("r3dhummingbird/DialoGPT-marxbot")
model = AutoModelWithLMHead.from_pretrained("r3dhummingbird/DialoGPT-marxbot")
# Let's chat for 4 lines
for step in r... |
DTAI-KULeuven/robbertje-39-gb-non-shuffled | 7111624edf031ee6da059ee1fbf9a7cb1ac04226 | 2021-08-13T10:51:47.000Z | [
"pytorch",
"tensorboard",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | DTAI-KULeuven | null | DTAI-KULeuven/robbertje-39-gb-non-shuffled | 28 | null | transformers | 7,304 | Entry not found |
EasthShin/BTS_Lyrics_GPT-Neo-base | 592c6518ee954f13614c550629b4f41af38ca6dc | 2021-08-09T05:52:07.000Z | [
"pytorch",
"gpt_neo",
"text-generation",
"transformers"
] | text-generation | false | EasthShin | null | EasthShin/BTS_Lyrics_GPT-Neo-base | 28 | null | transformers | 7,305 | Entry not found |
Helsinki-NLP/opus-mt-bi-en | feb365f89ee1f47cad4f1581896b80ae88978983 | 2021-09-09T21:27:44.000Z | [
"pytorch",
"marian",
"text2text-generation",
"bi",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-bi-en | 28 | null | transformers | 7,306 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-bi-en
* source languages: bi
* target languages: en
* OPUS readme: [bi-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/bi-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-mt-ca-pt | 272ac9087d98a17e9e9e0b6fe3628126e03e1099 | 2021-01-18T07:53:17.000Z | [
"pytorch",
"marian",
"text2text-generation",
"ca",
"pt",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-ca-pt | 28 | null | transformers | 7,307 | ---
language:
- ca
- pt
tags:
- translation
license: apache-2.0
---
### cat-por
* source group: Catalan
* target group: Portuguese
* OPUS readme: [cat-por](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/cat-por/README.md)
* model: transformer-align
* source language(s): cat
* target lang... |
Helsinki-NLP/opus-mt-en-tn | 39eecd8754063c0a82d0525386c3d8c6ed6df0db | 2021-09-09T21:39:57.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"tn",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-en-tn | 28 | null | transformers | 7,308 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-en-tn
* source languages: en
* target languages: tn
* OPUS readme: [en-tn](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/en-tn/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-mt-eo-fr | 3d9fb1c4184f318f966f65f1d6fbd9d3e7737d24 | 2021-09-09T21:41:01.000Z | [
"pytorch",
"marian",
"text2text-generation",
"eo",
"fr",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-eo-fr | 28 | null | transformers | 7,309 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-eo-fr
* source languages: eo
* target languages: fr
* OPUS readme: [eo-fr](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/eo-fr/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-mt-ny-en | 41bd8d14501ebfb32578c2daf169ed8f2f3ec5da | 2021-09-10T13:59:51.000Z | [
"pytorch",
"marian",
"text2text-generation",
"ny",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-ny-en | 28 | null | transformers | 7,310 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-ny-en
* source languages: ny
* target languages: en
* OPUS readme: [ny-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/ny-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-mt-sk-es | ce75e731abfa7c2d2991620c50c49cfbfb9c8ca2 | 2021-09-10T14:03:24.000Z | [
"pytorch",
"marian",
"text2text-generation",
"sk",
"es",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-sk-es | 28 | null | transformers | 7,311 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-sk-es
* source languages: sk
* target languages: es
* OPUS readme: [sk-es](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/sk-es/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-mt-ss-en | f98578726f54ad3d353a6b3cdbcbd71192567471 | 2021-09-10T14:04:47.000Z | [
"pytorch",
"marian",
"text2text-generation",
"ss",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-ss-en | 28 | null | transformers | 7,312 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-ss-en
* source languages: ss
* target languages: en
* OPUS readme: [ss-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/ss-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Ifromspace/GRIEFSOFT | ed74ab191da8b9bee8fc154393311e8463068c6a | 2022-01-15T13:06:43.000Z | [
"pytorch",
"gpt2",
"text-generation",
"ru",
"transformers",
"PyTorch",
"Transformers",
"4ulan"
] | text-generation | false | Ifromspace | null | Ifromspace/GRIEFSOFT | 28 | 1 | transformers | 7,313 | ---
language:
- ru
tags:
- PyTorch
- Transformers
- 4ulan
---
**Fork of https://huggingface.co/sberbank-ai/rugpt3large_based_on_gpt2**
Забавное для дискордика))00))
ROADMAP:
- Собираю датасетик из книжек про попаданцев. <------------------------- Сейчас тут.
- Дообучаю.
- Выбрасываю в дискордик.
https://discord.gg/... |
KBLab/electra-base-swedish-cased-generator | 9c12ede983d54e382381a3f1a471eab7fd2d244f | 2021-01-20T13:17:06.000Z | [
"pytorch",
"tf",
"electra",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | KBLab | null | KBLab/electra-base-swedish-cased-generator | 28 | null | transformers | 7,314 | Entry not found |
Lysa/subheading_generator_en | d54538df619bda7cba66deeaa18ae0ae812ee359 | 2021-06-13T17:24:28.000Z | [
"pytorch",
"jax",
"bart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | Lysa | null | Lysa/subheading_generator_en | 28 | null | transformers | 7,315 | Entry not found |
PaulAdversarial/T5_PAN_Hate_Speech_Twitter_topic_author_ishatespeach | c095fe8a019926dcd1387962b0056ba31a0c4959 | 2021-06-23T03:49:54.000Z | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | PaulAdversarial | null | PaulAdversarial/T5_PAN_Hate_Speech_Twitter_topic_author_ishatespeach | 28 | null | transformers | 7,316 | ##A T5ForConditionalGeneration trained on 3 tasks from PAN Profiling Hate Speech Spreaders on Twitter dataset (EN):
* author attribution (train and test sets from the PAN task)
* topic attribution - topics were assigned with BertTopic library using embeddings from `cardiffnlp/bertweet-base-hate` Roberta model (train a... |
SEBIS/code_trans_t5_large_code_documentation_generation_python_transfer_learning_finetune | 60d59123213538e47a6b07b2f4696a774d7c293e | 2021-06-23T07:46:32.000Z | [
"pytorch",
"jax",
"t5",
"feature-extraction",
"transformers",
"summarization"
] | summarization | false | SEBIS | null | SEBIS/code_trans_t5_large_code_documentation_generation_python_transfer_learning_finetune | 28 | null | transformers | 7,317 | ---
tags:
- summarization
widget:
- text: "def e ( message , exit_code = None ) : print_log ( message , YELLOW , BOLD ) if exit_code is not None : sys . exit ( exit_code )"
---
# CodeTrans model for code documentation generation python
Pretrained model on programming language python using the t5 large model architec... |
T-Systems-onsite/cross-de-fr-roberta-sentence-transformer | 646c4dfed1135b713568267a0b9b3be14a3f8d1c | 2022-06-28T19:56:37.000Z | [
"pytorch",
"tf",
"xlm-roberta",
"feature-extraction",
"fr",
"de",
"dataset:stsb_multi_mt",
"transformers",
"sentence_embedding",
"search",
"roberta",
"xlm-r-distilroberta-base-paraphrase-v1",
"license:mit"
] | feature-extraction | false | T-Systems-onsite | null | T-Systems-onsite/cross-de-fr-roberta-sentence-transformer | 28 | null | transformers | 7,318 | ---
language:
- fr
- de
license: mit
tags:
- sentence_embedding
- search
- pytorch
- xlm-roberta
- roberta
- xlm-r-distilroberta-base-paraphrase-v1
datasets:
- stsb_multi_mt
metrics:
- Spearman’s rank correlation
- cosine similarity
---
# Cross German & French RoBERTa for Sentence Embeddings
|
akhooli/gpt2-ar-poetry | 5da7539824e37c256bb30be15f8ec6eaf67c08d3 | 2021-05-21T12:34:58.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | akhooli | null | akhooli/gpt2-ar-poetry | 28 | null | transformers | 7,319 | Entry not found |
albertbn/gpt2-medium-finetuned-ads-fp16-blocksz512 | 818ae136d436ccb298c1a8d22cb31a9485ba5cea | 2021-05-21T12:44:25.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | albertbn | null | albertbn/gpt2-medium-finetuned-ads-fp16-blocksz512 | 28 | null | transformers | 7,320 | Entry not found |
anton-l/wav2vec2-large-xlsr-53-romanian | 2f1e970a98e68daeea93ffa17da566a05b05803c | 2021-07-05T20:20:21.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"ro",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | anton-l | null | anton-l/wav2vec2-large-xlsr-53-romanian | 28 | null | transformers | 7,321 | ---
language: ro
datasets:
- common_voice
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: Romanian XLSR Wav2Vec2 Large 53 by Anton Lozhkov
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
... |
bertin-project/bertin-base-random | 754d33bc2bb3227fc4e61cf4151b4bfbbc30986f | 2021-09-23T13:42:00.000Z | [
"pytorch",
"jax",
"tensorboard",
"joblib",
"roberta",
"fill-mask",
"es",
"transformers",
"spanish",
"license:cc-by-4.0",
"autotrain_compatible"
] | fill-mask | false | bertin-project | null | bertin-project/bertin-base-random | 28 | null | transformers | 7,322 | ---
language: es
license: cc-by-4.0
tags:
- spanish
- roberta
pipeline_tag: fill-mask
widget:
- text: Fui a la librería a comprar un <mask>.
---
This is a **RoBERTa-base** model trained from scratch in Spanish.
The training dataset is [mc4](https://huggingface.co/datasets/bertin-project/mc4-es-sampled ) subsampling d... |
bertin-project/bertin-base-stepwise-exp-512seqlen | 62feafbd538396054ae69497ac49f6a07a3f2e20 | 2021-09-23T13:42:03.000Z | [
"pytorch",
"jax",
"tensorboard",
"joblib",
"roberta",
"fill-mask",
"es",
"transformers",
"spanish",
"license:cc-by-4.0",
"autotrain_compatible"
] | fill-mask | false | bertin-project | null | bertin-project/bertin-base-stepwise-exp-512seqlen | 28 | null | transformers | 7,323 | ---
language: es
license: cc-by-4.0
tags:
- spanish
- roberta
pipeline_tag: fill-mask
widget:
- text: Fui a la librería a comprar un <mask>.
---
This is a **RoBERTa-base** model trained from scratch in Spanish.
The training dataset is [mc4](https://huggingface.co/datasets/bertin-project/mc4-es-sampled ) subsampling d... |
bertin-project/bertin-base-stepwise | 83a53bbd6807a25fc0dd8712e096b7501b2235bb | 2021-09-23T13:42:06.000Z | [
"pytorch",
"jax",
"tensorboard",
"joblib",
"roberta",
"fill-mask",
"es",
"transformers",
"spanish",
"license:cc-by-4.0",
"autotrain_compatible"
] | fill-mask | false | bertin-project | null | bertin-project/bertin-base-stepwise | 28 | null | transformers | 7,324 | ---
language: es
license: cc-by-4.0
tags:
- spanish
- roberta
pipeline_tag: fill-mask
widget:
- text: Fui a la librería a comprar un <mask>.
---
This is a **RoBERTa-base** model trained from scratch in Spanish.
The training dataset is [mc4](https://huggingface.co/datasets/bertin-project/mc4-es-sampled ) subsampling d... |
ccdv/lsg-pegasus-large-4096 | 9c4cb9f8f9ba229d5122302c010601a834553e22 | 2022-07-25T18:11:34.000Z | [
"pytorch",
"pegasus",
"text2text-generation",
"en",
"arxiv:1912.08777",
"transformers",
"summarization",
"long context",
"fill-mask",
"autotrain_compatible"
] | fill-mask | false | ccdv | null | ccdv/lsg-pegasus-large-4096 | 28 | null | transformers | 7,325 | ---
tags:
- summarization
- pegasus
- long context
language:
- en
pipeline_tag: fill-mask
---
# LSG model
**Transformers >= 4.18.0**\
**This model relies on a custom modeling file, you need to add trust_remote_code=True**\
**See [\#13467](https://github.com/huggingface/transformers/pull/13467)**
* [Usage](#usage)
* ... |
connorboyle/bert-ner-i2b2 | 9769589dd5855cf38172551d476dc4799de141f2 | 2021-12-01T00:13:39.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | connorboyle | null | connorboyle/bert-ner-i2b2 | 28 | 1 | transformers | 7,326 | Named-entity recognition model trained on the I2B2 training data set for PHI.
|
cross-encoder/msmarco-MiniLM-L12-en-de-v1 | 5d615f8f86798d9fb89dfd6d3fba53817acd45cf | 2021-08-05T08:40:18.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers",
"license:apache-2.0"
] | text-classification | false | cross-encoder | null | cross-encoder/msmarco-MiniLM-L12-en-de-v1 | 28 | null | transformers | 7,327 | ---
license: apache-2.0
---
# Cross-Encoder for MS MARCO - EN-DE
This is a cross-lingual Cross-Encoder model for EN-DE that can be used for passage re-ranking. It was trained on the [MS Marco Passage Ranking](https://github.com/microsoft/MSMARCO-Passage-Ranking) task.
The model can be used for Information Retrieval: ... |
cvcio/mediawatch-el-topics | 2ca63fb4f74ab3c8f5c2058cabe20f1c39d6197e | 2022-02-20T12:26:45.000Z | [
"pytorch",
"roberta",
"text-classification",
"el",
"transformers",
"Greek",
"news",
"license:gpl-3.0",
"model-index"
] | text-classification | false | cvcio | null | cvcio/mediawatch-el-topics | 28 | null | transformers | 7,328 | ---
language: el
license: gpl-3.0
tags:
- roberta
- Greek
- news
- transformers
- text-classification
pipeline_tag: text-classification
model-index:
- name: mediawatch-el-topics
results:
- task:
type: text-classification
name: Multi Label Text Classification
metrics:
- type: roc_auc
v... |
dbernsohn/roberta-javascript | bea9a1d2c8158136f315fb634c47bb34197db42e | 2021-05-20T15:55:17.000Z | [
"pytorch",
"jax",
"roberta",
"fill-mask",
"javascript",
"dataset:code_search_net",
"arxiv:1907.11692",
"transformers",
"autotrain_compatible"
] | fill-mask | false | dbernsohn | null | dbernsohn/roberta-javascript | 28 | null | transformers | 7,329 | # roberta-javascript
---
language: javascript
datasets:
- code_search_net
---
This is a [roberta](https://arxiv.org/pdf/1907.11692.pdf) pre-trained version on the [CodeSearchNet dataset](https://github.com/github/CodeSearchNet) for **javascript** Mask Language Model mission.
To load the model:
(necessary packages: !p... |
dingkun/retrievalv1 | f7b16d1a858f41554769fbebfd7b2ce8d598f420 | 2022-06-20T03:00:26.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | dingkun | null | dingkun/retrievalv1 | 28 | null | transformers | 7,330 | Entry not found |
emre/wav2vec-tr-lite-AG | 7e8302e4b06020fabfaf5d6dbcb86e7cb108a757 | 2021-12-10T22:46:25.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"tr",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | emre | null | emre/wav2vec-tr-lite-AG | 28 | null | transformers | 7,331 | ---
language: tr
datasets:
- common_voice
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 Turkish by Davut Emre TASAR
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common... |
hgw3lss/gpt-j-6B-Buckland | b460b2de16f21348418ca454c48893b6ff93a73d | 2022-02-12T15:31:01.000Z | [
"pytorch",
"gptj",
"text-generation",
"transformers"
] | text-generation | false | hgw3lss | null | hgw3lss/gpt-j-6B-Buckland | 28 | null | transformers | 7,332 | Entry not found |
huggingtweets/dril-fart-horse_ebooks | fb50047f0c95140282dd089e2ebe097ef4d83f8d | 2021-12-23T01:55:17.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/dril-fart-horse_ebooks | 28 | 1 | transformers | 7,333 | ---
language: en
thumbnail: http://www.huggingtweets.com/dril-fart-horse_ebooks/1640224513212/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-righ... |
huggingtweets/femoidfurry | b867b94353416af9144f5b7ff5d8a384e04dd769 | 2021-09-17T01:24:09.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/femoidfurry | 28 | null | transformers | 7,334 | ---
language: en
thumbnail: https://www.huggingtweets.com/femoidfurry/1631841845149/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; wi... |
huggingtweets/heatherchungus | 3c868dc96e6177dd8dc597b57155aadd7a1f17c8 | 2021-05-22T06:44:28.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/heatherchungus | 28 | null | transformers | 7,335 | ---
language: en
thumbnail: https://www.huggingtweets.com/heatherchungus/1617912956937/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/1376723854... |
huggingtweets/stockstotrade | e8bb1fe59d3d111de64994ff190b786983a7a740 | 2021-11-19T03:41:39.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/stockstotrade | 28 | null | transformers | 7,336 | ---
language: en
thumbnail: https://www.huggingtweets.com/stockstotrade/1637293295111/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; ... |
icelab/spaceroberta_CR | 4b002f0f633b57e112e14633c169ab7441d428a5 | 2022-02-16T09:30:10.000Z | [
"pytorch",
"roberta",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | icelab | null | icelab/spaceroberta_CR | 28 | null | transformers | 7,337 | ---
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)."
---
---
# spaceroberta_CR
## Model desciption
This is fine-tuned... |
kaesve/BERT_patent_reference_extraction | c9dcc71e951855ed35b5cd0f3def453794f540a4 | 2021-05-19T20:57:51.000Z | [
"pytorch",
"jax",
"bert",
"fill-mask",
"arxiv:2101.01039",
"transformers",
"autotrain_compatible"
] | fill-mask | false | kaesve | null | kaesve/BERT_patent_reference_extraction | 28 | null | transformers | 7,338 | # Reference extraction in patents
This repository contains a finetuned BERT 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. |
malay-huggingface/albert-tiny-bahasa-cased | 6d6150b8fabae7e55cffc7ace626111bb8a67f2e | 2021-09-26T12:37:13.000Z | [
"pytorch",
"albert",
"fill-mask",
"ms",
"transformers",
"autotrain_compatible"
] | fill-mask | false | malay-huggingface | null | malay-huggingface/albert-tiny-bahasa-cased | 28 | null | transformers | 7,339 | ---
language: ms
---
# albert-tiny-bahasa-cased
Pretrained ALBERT tiny language model for Malay.
## Pretraining Corpus
`albert-tiny-bahasa-cased` model was pretrained on ~1.4 Billion words. Below is list of data we trained on,
1. [cleaned local texts](https://github.com/huseinzol05/malay-dataset/tree/master/dumpin... |
microsoft/unispeech-sat-base-100h-libri-ft | b294556d8d77cc539f9d08bef0ddbb0f60985328 | 2021-11-04T15:26:40.000Z | [
"pytorch",
"unispeech-sat",
"automatic-speech-recognition",
"en",
"dataset:librispeech_asr",
"arxiv:2110.05752",
"transformers",
"audio",
"license:apache-2.0"
] | automatic-speech-recognition | false | microsoft | null | microsoft/unispeech-sat-base-100h-libri-ft | 28 | 3 | transformers | 7,340 | ---
language: en
datasets:
- librispeech_asr
tags:
- audio
- automatic-speech-recognition
license: apache-2.0
widget:
- example_title: Librispeech sample 1
src: https://cdn-media.huggingface.co/speech_samples/sample1.flac
- example_title: Librispeech sample 2
src: https://cdn-media.huggingface.co/speech_samples/sam... |
mlcorelib/deberta-base-uncased | 190353c0376b3a54214228847caa4979f99ec99a | 2021-05-01T12:33:45.000Z | [
"pytorch",
"tf",
"jax",
"rust",
"bert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1810.04805",
"transformers",
"exbert",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | mlcorelib | null | mlcorelib/deberta-base-uncased | 28 | null | transformers | 7,341 | ---
language: en
tags:
- exbert
license: apache-2.0
datasets:
- bookcorpus
- wikipedia
---
# BERT base model (uncased)
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](http... |
mudes/en-base | 1600298e0458d961c2c749da7a098f69b4be478a | 2021-05-20T01:03:44.000Z | [
"pytorch",
"jax",
"bert",
"token-classification",
"en",
"arxiv:2102.09665",
"arxiv:2104.04630",
"transformers",
"mudes",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | false | mudes | null | mudes/en-base | 28 | 1 | transformers | 7,342 | ---
language: en
tags:
- mudes
license: apache-2.0
---
# MUDES - {Mu}ltilingual {De}tection of Offensive {S}pans
We provide state-of-the-art models to detect toxic spans in social media texts. We introduce our framework in [this paper](https://arxiv.org/abs/2102.09665). We have evaluated our models on Toxic Spans tas... |
ncoop57/multi-code-clippy | 380fc6200e5aa4fbf17dc696d23f29cfdfea8d58 | 2022-03-03T12:44:46.000Z | [
"pytorch",
"gpt_neo",
"text-generation",
"transformers"
] | text-generation | false | ncoop57 | null | ncoop57/multi-code-clippy | 28 | null | transformers | 7,343 | Entry not found |
nepp1d0/ChemBERTa_drug_state_classification | 080708b8d69082d295aa88ccbec56b33a4205501 | 2022-04-13T18:27:48.000Z | [
"pytorch",
"tensorboard",
"roberta",
"text-classification",
"transformers",
"generated_from_trainer",
"model-index"
] | text-classification | false | nepp1d0 | null | nepp1d0/ChemBERTa_drug_state_classification | 28 | null | transformers | 7,344 | ---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ChemBERTa_drug_state_classification
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. -->
#... |
othrif/wav2vec2-large-xlsr-arabic | 28096ade748ce453de4df34305836c6f2167178f | 2021-03-29T18:43:31.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ar",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | othrif | null | othrif/wav2vec2-large-xlsr-arabic | 28 | null | transformers | 7,345 | ---
language: ar
datasets:
- common_voice
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 Arabic by Othmane Rifki
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset... |
pere/norwegian-gpt2 | be4f5522d2d7f5274d4800eb0579dab3102b0a09 | 2021-09-23T16:19:24.000Z | [
"pytorch",
"jax",
"tensorboard",
"gpt2",
"text-generation",
"no",
"dataset:oscar",
"transformers",
"norwegian",
"GPT2",
"casual language modeling",
"license:cc-by-4.0"
] | text-generation | false | pere | null | pere/norwegian-gpt2 | 28 | null | transformers | 7,346 | ---
language: no
license: cc-by-4.0
tags:
- norwegian
- GPT2
- casual language modeling
datasets:
- oscar
---
# Norwegian GPT-2 - Oscar
## Description
This is a sample reference model trained only on the Oscar Corpus for a day on a TPU v3-8. Pretrained model on Norwegian language using a causal language modeling (CL... |
phiyodr/bert-large-finetuned-squad2 | 5f4b89a4f92c4c975bb405548fc62869dc70f312 | 2021-05-20T02:36:12.000Z | [
"pytorch",
"jax",
"bert",
"question-answering",
"en",
"dataset:squad2",
"arxiv:1810.04805",
"arxiv:1806.03822",
"transformers",
"autotrain_compatible"
] | question-answering | false | phiyodr | null | phiyodr/bert-large-finetuned-squad2 | 28 | null | transformers | 7,347 | ---
language: en
tags:
- pytorch
- question-answering
datasets:
- squad2
metrics:
- exact
- f1
widget:
- text: "What discipline did Winkelmann create?"
context: "Johann Joachim Winckelmann was a German art historian and archaeologist. He was a pioneering Hellenist who first articulated the difference between Greek, G... |
ponmari/QuestionAnsweingBert | f501022178b31ab2063d14f88af895c0d7c5a127 | 2021-05-20T02:51:30.000Z | [
"pytorch",
"jax",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | ponmari | null | ponmari/QuestionAnsweingBert | 28 | null | transformers | 7,348 | Entry not found |
pradhyra/AWSBlogBert | 4ab2eb2471755ab5a1cbbd5d2767ba3efbae3b3a | 2021-05-20T19:30:09.000Z | [
"pytorch",
"jax",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | pradhyra | null | pradhyra/AWSBlogBert | 28 | null | transformers | 7,349 | This model is pre-trained on blog articles from AWS Blogs.
## Pre-training corpora
The input text contains around 3000 blog articles on [AWS Blogs website](https://aws.amazon.com/blogs/) technical subject matter including AWS products, tools and tutorials.
## Pre-training details
I picked a Roberta architecture for ... |
pstroe/roberta-base-latin-cased | cfcf8c2ac7b0cc5c627a1dafa23e0ba8fc2eed16 | 2021-12-06T09:10:49.000Z | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | pstroe | null | pstroe/roberta-base-latin-cased | 28 | null | transformers | 7,350 | ## RoBERTa Latin model
This is a Latin RoBERTa-based LM model.
The data it uses is the same as has been used to compute the text referenced HTR evaluation measures.
The intention of the Transformer-based LM is twofold: on the one hand, it will be used for the evaluation of HTR results, on the other, it should be use... |
sismetanin/rubert_conversational-ru-sentiment-rureviews | 6544d966bcbd5ab089438caf711e7394d8d1cdd2 | 2021-05-20T06:20:54.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"ru",
"transformers",
"sentiment analysis",
"Russian"
] | text-classification | false | sismetanin | null | sismetanin/rubert_conversational-ru-sentiment-rureviews | 28 | null | transformers | 7,351 | ---
language:
- ru
tags:
- sentiment analysis
- Russian
---
## RuBERT-Conversational-ru-sentiment-RuReviews
RuBERT-Conversational-ru-sentiment-RuReviews is a [RuBERT-Conversational](https://huggingface.co/DeepPavlov/rubert-base-cased-conversational) model fine-tuned on [RuReviews dataset](https://github.com/sismetan... |
sshleifer/student_cnn_12_6 | d266f51bbf3b5df7d91a640820a341770ae7ab45 | 2021-06-14T08:36:40.000Z | [
"pytorch",
"jax",
"bart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | sshleifer | null | sshleifer/student_cnn_12_6 | 28 | null | transformers | 7,352 | Entry not found |
textattack/albert-base-v2-rotten-tomatoes | b19b7cd9422f089722c7b7417e6a13ef2c2ac963 | 2020-07-06T16:35:34.000Z | [
"pytorch",
"albert",
"text-classification",
"transformers"
] | text-classification | false | textattack | null | textattack/albert-base-v2-rotten-tomatoes | 28 | null | transformers | 7,353 | ## TextAttack Model Card
This `albert-base-v2` model was fine-tuned for sequence classification using TextAttack
and the rotten_tomatoes dataset loaded using the `nlp` library. The model was fine-tuned
for 5 epochs with a batch size of 64, a learning
rate of 2e-05, and a maximum sequence length of 128.
Since this w... |
textattack/facebook-bart-large-QNLI | 00434bfe2b7e6a3bfcf34024f642ef519f0a0fe1 | 2020-06-09T16:50:26.000Z | [
"pytorch",
"bart",
"text-classification",
"transformers"
] | text-classification | false | textattack | null | textattack/facebook-bart-large-QNLI | 28 | null | transformers | 7,354 | Entry not found |
tog/fr-boris-8bit | 15191226465af9f10024d696f93f5090376ead9d | 2022-01-26T07:03:25.000Z | [
"pytorch",
"gptj",
"text-generation",
"transformers"
] | text-generation | false | tog | null | tog/fr-boris-8bit | 28 | null | transformers | 7,355 | Entry not found |
uer/chinese_roberta_L-10_H-768 | 6ab354686e240c51eb0c6203ec67fa1b7f0fc41a | 2022-07-15T08:15:19.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"zh",
"dataset:CLUECorpusSmall",
"arxiv:1909.05658",
"arxiv:1908.08962",
"transformers",
"autotrain_compatible"
] | fill-mask | false | uer | null | uer/chinese_roberta_L-10_H-768 | 28 | 2 | transformers | 7,356 | ---
language: zh
datasets: CLUECorpusSmall
widget:
- text: "北京是[MASK]国的首都。"
---
# Chinese RoBERTa Miniatures
## Model description
This is the set of 24 Chinese RoBERTa models pre-trained by [UER-py](https://github.com/dbiir/UER-py/), which is introduced in [this paper](https://arxiv.org/abs/1909.05658).
[Turc e... |
yhavinga/gpt-neo-125M-dutch | 863872afb9d8299aeb1b45ab7ef2cf2b0b248624 | 2022-03-20T10:21:20.000Z | [
"pytorch",
"jax",
"tensorboard",
"gpt_neo",
"text-generation",
"nl",
"dataset:yhavinga/mc4_nl_cleaned",
"transformers",
"gpt2-medium",
"gpt2"
] | text-generation | false | yhavinga | null | yhavinga/gpt-neo-125M-dutch | 28 | 1 | transformers | 7,357 | ---
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:
- gpt2-medium
- gpt2
pipeline_tag: text-generation
datasets:
- yha... |
vocab-transformers/cross_encoder-msmarco-distilbert-word2vec256k-MLM_785k_emb_updated | 8e5cdfd34a1bce3bfcbc6d2a4c4294ddb2e32c34 | 2022-02-25T12:44:23.000Z | [
"pytorch",
"distilbert",
"text-classification",
"transformers"
] | text-classification | false | vocab-transformers | null | vocab-transformers/cross_encoder-msmarco-distilbert-word2vec256k-MLM_785k_emb_updated | 28 | null | transformers | 7,358 | #cross_encoder-msmarco-distilbert-word2vec256k-MLM_785k_emb_updated
This CrossEncoder was trained with MarginMSE loss from the [vocab-transformers/msmarco-distilbert-word2vec256k-MLM_785k_emb_updated](https://hf.co/vocab-transformers/msmarco-distilbert-word2vec256k-MLM_785k_emb_updated) checkpoint. **Word embedding ... |
jweb/japanese-soseki-gpt2-1b | de9952d7bd8ad68f4e37e84c919ffbf31f909bcc | 2022-03-06T02:17:59.000Z | [
"pytorch",
"rust",
"gpt2",
"text-generation",
"ja",
"dataset:cc100",
"dataset:wikipedia",
"dataset:AozoraBunko",
"transformers",
"japanese",
"lm",
"nlp",
"rust-bert",
"license:mit"
] | text-generation | false | jweb | null | jweb/japanese-soseki-gpt2-1b | 28 | 2 | transformers | 7,359 | ---
language: ja
thumbnail: https://github.com/ycat3/japanese-pretrained-models/blob/master/jweb.png
tags:
- ja
- japanese
- gpt2
- text-generation
- lm
- nlp
- rust
- rust-bert
license: mit
datasets:
- cc100
- wikipedia
- AozoraBunko
widget:
- text: "夏目漱石は、"
---
# japanese-soseki-gpt2-1b
... |
hackathon-pln-es/poem-gen-spanish-t5-small | 7ef2e7df3e03360866d2e394dc3e5d36fb3e0e67 | 2022-04-03T03:30:07.000Z | [
"pytorch",
"tensorboard",
"t5",
"text2text-generation",
"es",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | hackathon-pln-es | null | hackathon-pln-es/poem-gen-spanish-t5-small | 28 | 4 | transformers | 7,360 | ---
license: mit
language: es
tags:
- generated_from_trainer
model-index:
- name: poem-gen-spanish-t5-small
results: []
---
# poem-gen-spanish-t5-small
This model is a fine-tuned version of [flax-community/spanish-t5-small](https://huggingface.co/flax-community/spanish-t5-small) on the [Spanish Poetry Dataset](http... |
hackathon-pln-es/twitter_sexismo-finetuned-exist2021-metwo | abb1735fa8735c95c2241b7f074af79592181a42 | 2022-05-18T08:48:34.000Z | [
"pytorch",
"roberta",
"text-classification",
"dataset:EXIST Dataset",
"dataset:MeTwo Machismo and Sexism Twitter Identification dataset",
"transformers",
"license:apache-2.0",
"model-index"
] | text-classification | false | hackathon-pln-es | null | hackathon-pln-es/twitter_sexismo-finetuned-exist2021-metwo | 28 | 4 | transformers | 7,361 | ---
license: apache-2.0
tags:
-
datasets:
- EXIST Dataset
- MeTwo Machismo and Sexism Twitter Identification dataset
widget:
- text: "manejas muy bien para ser mujer"
- text: "En temas políticos hombres y mujeres son iguales"
- text: "Los ipad son unos equipos electrónicos"
metrics:
- accuracy
model-index:
- name: t... |
huggingtweets/twitter | 5926a658115bb8084687850aaa93f7948b80d104 | 2022-03-21T13:19:21.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/twitter | 28 | 1 | transformers | 7,362 | ---
language: en
thumbnail: http://www.huggingtweets.com/twitter/1647868756403/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; width: ... |
Graphcore/gpt2-medium-wikitext-103 | 31d8e00b7ba45dd878a827682915499075720c88 | 2022-05-25T18:14:00.000Z | [
"pytorch",
"gpt2",
"text-generation",
"dataset:wikitext",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-generation | false | Graphcore | null | Graphcore/gpt2-medium-wikitext-103 | 28 | null | transformers | 7,363 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wikitext
model-index:
- name: clm_output_medium
results: []
---
# Graphcore/gpt2-medium-wikitext-103
Optimum Graphcore is a new open-source library and toolkit that enables developers to access IPU-optimized models certified by Hugging Face. It is ... |
Hieu/nft_label | 608833128e19b254f93934cd7583c25486051b83 | 2022-04-03T07:54:51.000Z | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | Hieu | null | Hieu/nft_label | 28 | null | transformers | 7,364 | Entry not found |
enimai/OPUS-mt-en-fr-finetuned-MUST-C | 8f20e7c89a406842044245e660e0aaaea812e491 | 2022-04-04T11:49:17.000Z | [
"pytorch",
"marian",
"text2text-generation",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | enimai | null | enimai/OPUS-mt-en-fr-finetuned-MUST-C | 28 | null | transformers | 7,365 | ---
license: apache-2.0
---
|
Raychanan/Longformer_Conflict | 0f40ee73ab18680bc5d63ce24f7aa74f1cbcb93b | 2022-04-16T15:30:07.000Z | [
"pytorch",
"tensorboard",
"longformer",
"text-classification",
"transformers"
] | text-classification | false | Raychanan | null | Raychanan/Longformer_Conflict | 28 | null | transformers | 7,366 | training_args = TrainingArguments(
output_dir="./results",
learning_rate=5e-5,
per_device_train_batch_size=1,
per_device_eval_batch_size=1,
num_train_epochs=5,
weight_decay=0.01,
evaluation_strategy="epoch",
push_to_hub=True
) |
engmatic-earth/mt5-zh-ja-en-trimmed-fine-tuned-v1 | 084211407f80d39ccc9e8c75817a8b77f1bbccae | 2022-04-17T11:00:50.000Z | [
"pytorch",
"tensorboard",
"mt5",
"text2text-generation",
"transformers",
"translation",
"generated_from_trainer",
"license:cc-by-nc-sa-4.0",
"model-index",
"autotrain_compatible"
] | translation | false | engmatic-earth | null | engmatic-earth/mt5-zh-ja-en-trimmed-fine-tuned-v1 | 28 | null | transformers | 7,367 | ---
license: cc-by-nc-sa-4.0
tags:
- translation
- generated_from_trainer
metrics:
- bleu
model-index:
- name: mt5-zh-ja-en-trimmed-fine-tuned-v1
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it... |
athairus/m2m100_418M_finetuned_litk_es_en | 224f5caa9f9d7dc207dc96f636b595b26bdb49f6 | 2022-04-17T19:30:02.000Z | [
"pytorch",
"m2m_100",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | athairus | null | athairus/m2m100_418M_finetuned_litk_es_en | 28 | null | transformers | 7,368 | Entry not found |
xfbai/AMRBART-large-finetuned-AMR2.0-AMRParsing | 2d1fc8be6bfb98266e944718a0ad61743707aaef | 2022-04-26T05:51:03.000Z | [
"pytorch",
"bart",
"text2text-generation",
"en",
"arxiv:2203.07836",
"transformers",
"AMRBART",
"license:mit",
"autotrain_compatible"
] | text2text-generation | false | xfbai | null | xfbai/AMRBART-large-finetuned-AMR2.0-AMRParsing | 28 | 1 | transformers | 7,369 | ---
language: en
tags:
- AMRBART
license: mit
---
## AMRBART-large-finetuned-AMR2.0-AMRParsing
This model is a fine-tuned version of [AMRBART-large](https://huggingface.co/xfbai/AMRBART-large) on an AMR2.0 dataset. It achieves a Smatch of 85.4 on the evaluation set: More details are introduced in the paper: [Graph Pr... |
CEBaB/bert-base-uncased.CEBaB.sa.5-class.exclusive.seed_77 | ca8a529c4808f6f60d9b6c451fb43bb157cc305e | 2022-05-11T01:40:16.000Z | [
"pytorch",
"bert",
"transformers"
] | null | false | CEBaB | null | CEBaB/bert-base-uncased.CEBaB.sa.5-class.exclusive.seed_77 | 28 | null | transformers | 7,370 | Entry not found |
CEBaB/bert-base-uncased.CEBaB.sa.5-class.exclusive.seed_88 | 4bf0792fca5708c74d1f6557a4ea8d4d88837ad7 | 2022-05-11T02:32:22.000Z | [
"pytorch",
"bert",
"transformers"
] | null | false | CEBaB | null | CEBaB/bert-base-uncased.CEBaB.sa.5-class.exclusive.seed_88 | 28 | null | transformers | 7,371 | Entry not found |
dragonSwing/vibert-capu | 5859a7baaa9ed2d6f7923e54f570b0ff94b566c5 | 2022-05-17T15:02:30.000Z | [
"pytorch",
"bert",
"vi",
"dataset:oscar-corpus/OSCAR-2109",
"transformers",
"capitalization",
"punctuation",
"token-classification",
"license:cc-by-sa-4.0"
] | token-classification | false | dragonSwing | null | dragonSwing/vibert-capu | 28 | null | transformers | 7,372 | ---
language:
- vi
tags:
- capitalization
- punctuation
- token-classification
license: cc-by-sa-4.0
datasets:
- oscar-corpus/OSCAR-2109
metrics:
- accuracy
- precision
- recall
- f1
---
# ✨ vibert-capitalization-punctuation
This a [viBERT](https://huggingface.co/FPTAI/vibert-base-cased) model finetuned for punctuation... |
ncfrey/ChemGPT-1.2B | 0164ca1f1754cd36b43c34b185373ee3672e7d65 | 2022-06-15T15:44:24.000Z | [
"pytorch",
"gpt_neo",
"text-generation",
"transformers",
"chemistry"
] | text-generation | false | ncfrey | null | ncfrey/ChemGPT-1.2B | 28 | 1 | transformers | 7,373 | ---
tags:
- chemistry
---
# ChemGPT 1.2B
ChemGPT is based on the GPT-Neo model and was introduced in the paper [Neural Scaling of Deep Chemical Models](https://chemrxiv.org/engage/chemrxiv/article-details/627bddd544bdd532395fb4b5).
## Model description
ChemGPT is a transformers model for generative molecular modelin... |
VMware/vbert-2021-base | dcdbfcad3a2d87d1083659cab9ff44abc2cb1661 | 2022-06-16T22:27:04.000Z | [
"pytorch",
"tf",
"bert",
"fill-mask",
"eng",
"transformers",
"tensorflow",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | VMware | null | VMware/vbert-2021-base | 28 | 2 | transformers | 7,374 | ---
language:
- "eng"
thumbnail: "url to a thumbnail used in social sharing"
tags:
- "pytorch"
- "tensorflow"
license: "apache-2.0"
---
# vBERT-2021-BASE
### Model Info:
<ul>
<li> Authors: R&D AI Lab, VMware Inc.
<li> Model date: April, 2022
<li> Model version: 2021-base
<li> Model type: Pretrained language mode... |
anuj55/paraphrase-mpnet-base-v2-finetuned-polifact | b7669ce7827236d430928c4bc1d0ca7a11eeb70a | 2022-05-16T20:56:23.000Z | [
"pytorch",
"tensorboard",
"mpnet",
"text-classification",
"transformers"
] | text-classification | false | anuj55 | null | anuj55/paraphrase-mpnet-base-v2-finetuned-polifact | 28 | null | transformers | 7,375 | Entry not found |
sabersol/bert-base-uncased-emotion | f80494fad3c80a265ce6fde5816f2c4549067e2d | 2022-05-27T03:25:49.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers",
"license:cc-by-nc-sa-4.0"
] | text-classification | false | sabersol | null | sabersol/bert-base-uncased-emotion | 28 | null | transformers | 7,376 | ---
license: cc-by-nc-sa-4.0
---
# CITDA:
Fine-tuned `bert-base-uncased` on the `emotions` dataset
Demo Notebook: https://colab.research.google.com/drive/10ZCFvlf2UV3FjU4ymf4OoipQvqHbIItG?usp=sharing
## Packages
- Install `torch`
- Also, `pip install transformers datasets scikit-learn wandb seaborn python-dotenv`
... |
north/t5_xxl_NCC_lm | eb2f5bf7a7b0f25372eb9ab0f1968d34240589b8 | 2022-06-01T19:42:09.000Z | [
"pytorch",
"tensorboard",
"t5",
"text2text-generation",
"no",
"nn",
"sv",
"dk",
"is",
"en",
"dataset:nbailab/NCC",
"dataset:mc4",
"dataset:wikipedia",
"arxiv:2104.09617",
"arxiv:1910.10683",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | north | null | north/t5_xxl_NCC_lm | 28 | null | transformers | 7,377 | ---
language:
- no
- nn
- sv
- dk
- is
- en
datasets:
- nbailab/NCC
- mc4
- wikipedia
widget:
- text: <extra_id_0> hver uke samles Regjeringens medlemmer til Statsråd på <extra_id_1>. Dette organet er øverste <extra_id_2> i Norge. For at møtet skal være <extra_id_3>, må over halvparten av regjeringens <extra_id_4> ... |
tursunali/bpt2 | 9ca6484cc1837f3c3ec5fec57dcb4b9ddf37e246 | 2022-05-24T04:12:13.000Z | [
"pytorch",
"gpt2",
"text-generation",
"de",
"transformers"
] | text-generation | false | tursunali | null | tursunali/bpt2 | 28 | null | transformers | 7,378 | ---
language: de
widget:
- text: "In einer schockierenden Entdeckung fanden Wissenschaftler eine Herde Einhörner, die in einem abgelegenen, zuvor unerforschten Tal in den Anden lebten."
---
# BPT2
See the [GPT2 model card](https://huggingface.co/gpt2) for considerations on limitations and bias. See the [GPT2 documen... |
sharif-dal/dal-bert | ff8842a0a2f50f5c07343d37acf02dd29ccef19b | 2022-07-02T10:18:35.000Z | [
"pytorch",
"bert",
"fill-mask",
"fa",
"arxiv:1810.04805",
"transformers",
"bert-fa",
"bert-persian",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | fill-mask | false | sharif-dal | null | sharif-dal/dal-bert | 28 | 2 | transformers | 7,379 | ---
license: apache-2.0
language: fa
widget:
- text: "از هر دستی بگیری از همون [MASK] میدی"
- text: "این آخرین باره بهت [MASK] میگم"
- text: 'چرا آن جوان بیچاره را به سخره [MASK]'
- text: 'آخه محسن [MASK] هم شد خواننده؟'
- text: 'پسر عجب [MASK] زد'
tags:
- bert-fa
- bert-persian
model-index:
- name: dal-bert
res... |
finiteautomata/ner-leg | d857431dae1ae112d4dcdb6533c55f6e256d8eec | 2022-06-22T13:45:53.000Z | [
"pytorch",
"distilbert",
"token-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | finiteautomata | null | finiteautomata/ner-leg | 28 | null | transformers | 7,380 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
model-index:
- name: ner-leg
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 co... |
RUCAIBox/mvp-multi-task | 2462b3c380379dbdc99dfb058f51e35f084b29e1 | 2022-06-27T02:27:55.000Z | [
"pytorch",
"mvp",
"en",
"arxiv:2206.12131",
"transformers",
"text-generation",
"text2text-generation",
"summarization",
"conversational",
"license:apache-2.0"
] | text2text-generation | false | RUCAIBox | null | RUCAIBox/mvp-multi-task | 28 | null | transformers | 7,381 | ---
license: apache-2.0
language:
- en
tags:
- text-generation
- text2text-generation
- summarization
- conversational
pipeline_tag: text2text-generation
widget:
- text: "Summarize: You may want to stick it to your boss and leave your job, but don't do it if these are your reasons."
example_title: "Summarization"
- t... |
vaibhavagg303/T5-test | edbff64988ee98cf29620c17a7b09eb60f808b81 | 2022-06-08T04:48:32.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | vaibhavagg303 | null | vaibhavagg303/T5-test | 28 | null | transformers | 7,382 | Entry not found |
edmundhui/mental_health_trainer | 0ea11c1763041dbbb02eff39e023a4b0b58e5ceb | 2022-06-21T20:41:48.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | edmundhui | null | edmundhui/mental_health_trainer | 28 | null | transformers | 7,383 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: mental_health_trainer
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# mental_health... |
santiviquez/ssr-base-finetuned-samsum-en | 61500501e1d281dbbdb20fb598a19dc4fd94fb36 | 2022-06-27T20:54:46.000Z | [
"pytorch",
"tensorboard",
"t5",
"text2text-generation",
"dataset:samsum",
"transformers",
"summarization",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | summarization | false | santiviquez | null | santiviquez/ssr-base-finetuned-samsum-en | 28 | null | transformers | 7,384 | ---
tags:
- summarization
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: ssr-base-finetuned-samsum-en
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: samsum
type: samsum
args: samsum
metr... |
lakshaywadhwa1993/ner_marathi_bert | 060094605f07021b0c3b465affc54b6bc5179adc | 2022-06-09T22:01:58.000Z | [
"pytorch",
"bert",
"token-classification",
"mr",
"dataset:wikiann",
"transformers",
"autotrain_compatible"
] | token-classification | false | lakshaywadhwa1993 | null | lakshaywadhwa1993/ner_marathi_bert | 28 | null | transformers | 7,385 | ---
language: mr
datasets:
- wikiann
examples:
widget:
- text: "राज्यसभा निवडणुकांसाठी उद्या मुंबईत मतदान होणार आहे."
example_title: "Sentence_1"
- text: "विराट कोहली भारताकडून खेळतो."
example_title: "Sentence_2"
- text: "नवी दिल्ली ही भारताची राजधानी आहे"
example_title: "Sentence_3"
---
<h1>Marathi Named Entity... |
nikitakotsehub/AirlineDistilBERT | 2a72ac93509aac84926c484b40f4001bdad75f43 | 2022-06-13T22:14:42.000Z | [
"pytorch",
"distilbert",
"text-classification",
"transformers"
] | text-classification | false | nikitakotsehub | null | nikitakotsehub/AirlineDistilBERT | 28 | null | transformers | 7,386 | Entry not found |
waboucay/camembert-large-finetuned-repnum_wl-rua_wl | e0b3eb6d8ddaf13f50d9359a010f98176c7e96a7 | 2022-06-16T07:36:43.000Z | [
"pytorch",
"camembert",
"text-classification",
"fr",
"transformers",
"nli"
] | text-classification | false | waboucay | null | waboucay/camembert-large-finetuned-repnum_wl-rua_wl | 28 | null | transformers | 7,387 | ---
language:
- fr
tags:
- nli
metrics:
- f1
---
## Eval results
We obtain the following results on ```validation``` and ```test``` sets:
| Set | F1<sub>micro</sub> | F1<sub>macro</sub> |
|------------|--------------------|--------------------|
| validation | 84.5 | 84.3 |
| test ... |
AlekseyKorshuk/results-gpt-j-base-erotic | 7f4cefe2dea30658129b8ad67288809c0e1bdbab | 2022-06-18T13:21:51.000Z | [
"pytorch",
"gptj",
"text-generation",
"transformers"
] | text-generation | false | AlekseyKorshuk | null | AlekseyKorshuk/results-gpt-j-base-erotic | 28 | null | transformers | 7,388 | Entry not found |
nilaB97/bertweet-refugee | bf8eee7bcf3f8763b976e169113ad080fd953847 | 2022-07-01T15:02:51.000Z | [
"pytorch",
"tensorboard",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | nilaB97 | null | nilaB97/bertweet-refugee | 28 | null | transformers | 7,389 | Entry not found |
sumitrsch/muril_large_multiconer22_hi | ef3ad6981100da40dc26be41faed2ff8ad42e277 | 2022-07-02T17:46:01.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"license:afl-3.0",
"autotrain_compatible"
] | token-classification | false | sumitrsch | null | sumitrsch/muril_large_multiconer22_hi | 28 | 3 | transformers | 7,390 | ---
license: afl-3.0
---
This model is fine-tuned for Multiconer22 task on Hindi dataset.
hi_test.csv is preprocessed Hindi test dataset, which conll format is provided by Multiconer22 task.
This model can predict NER tag for Hindi sentnces using colab notebook https://colab.research.google.com/drive/17WyqwdoRNnz... |
sanjay-m1/grammar-corrector-v2 | caddb28d7ad2ef60025b1fc783e876dd22a51413 | 2022-06-26T19:10:37.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | sanjay-m1 | null | sanjay-m1/grammar-corrector-v2 | 28 | null | transformers | 7,391 | **This model is part of the Gramformer library** please refer to https://github.com/PrithivirajDamodaran/Gramformer/
|
nvidia/stt_fr_conformer_transducer_large | 65327ea5af70df919fa11ca4a8436c54ae67bd28 | 2022-06-30T19:59:08.000Z | [
"nemo",
"fr",
"dataset:multilingual_librispeech",
"dataset:mozilla-foundation/common_voice_7_0",
"dataset:VoxPopuli",
"arxiv:2005.08100",
"automatic-speech-recognition",
"speech",
"audio",
"Transducer",
"Conformer",
"Transformer",
"pytorch",
"NeMo",
"hf-asr-leaderboard",
"license:cc-by... | automatic-speech-recognition | false | nvidia | null | nvidia/stt_fr_conformer_transducer_large | 28 | 3 | nemo | 7,392 | ---
language:
- fr
library_name: nemo
datasets:
- multilingual_librispeech
- mozilla-foundation/common_voice_7_0
- VoxPopuli
thumbnail: null
tags:
- automatic-speech-recognition
- speech
- audio
- Transducer
- Conformer
- Transformer
- pytorch
- NeMo
- hf-asr-leaderboard
license: cc-by-4.0
model-index:
- name: stt_fr_c... |
KhawajaAbaid/distilbert-base-uncased-finetuned-emotion | 8088786fb2543691734f75c98ef39c4411f64acc | 2022-06-30T08:50:26.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"transformers"
] | text-classification | false | KhawajaAbaid | null | KhawajaAbaid/distilbert-base-uncased-finetuned-emotion | 28 | null | transformers | 7,393 | Entry not found |
Abdelmageed95/opt-125m-economy-data | 4ba66696a31d3f981882b9f737bb9367571bfdd2 | 2022-07-01T16:11:10.000Z | [
"pytorch",
"tensorboard",
"opt",
"text-generation",
"transformers",
"generated_from_trainer",
"license:other",
"model-index"
] | text-generation | false | Abdelmageed95 | null | Abdelmageed95/opt-125m-economy-data | 28 | null | transformers | 7,394 | ---
license: other
tags:
- generated_from_trainer
model-index:
- name: opt-125m-economy-data
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. -->
# opt-125m-economy-d... |
emilys/twitter-roberta-base-dec2021-CoNLL | 490838dbd0cd6511ccbf9039aaa7d79c69e5e88a | 2022-07-05T20:09:58.000Z | [
"pytorch",
"roberta",
"token-classification",
"dataset:conll2003",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | token-classification | false | emilys | null | emilys/twitter-roberta-base-dec2021-CoNLL | 28 | null | transformers | 7,395 | ---
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: twitter-roberta-base-dec2021-CoNLL
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type: conll2003
args: conll... |
luztraplet/roberta-large-finetuned-boolq | 7518bfb59bf6a5c0e40fee46314f7a99e95951c0 | 2022-07-06T15:49:23.000Z | [
"pytorch",
"roberta",
"text-classification",
"dataset:boolq",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index"
] | text-classification | false | luztraplet | null | luztraplet/roberta-large-finetuned-boolq | 28 | null | transformers | 7,396 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- boolq
model-index:
- name: roberta-large-finetuned-boolq
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. -... |
nielsr/videomae-base-short | 086f2e2091dba2e533fc324bddb3ef3a2d1c7692 | 2022-07-08T15:21:42.000Z | [
"pytorch",
"videomae",
"transformers"
] | null | false | nielsr | null | nielsr/videomae-base-short | 28 | null | transformers | 7,397 | Entry not found |
pyronear/mobilenet_v3_small | a6a0b39ca1f5b0a247eb0a2e83f06cd95fc03674 | 2022-07-17T23:48:39.000Z | [
"pytorch",
"onnx",
"dataset:pyronear/openfire",
"arxiv:1905.02244",
"transformers",
"image-classification",
"license:apache-2.0"
] | image-classification | false | pyronear | null | pyronear/mobilenet_v3_small | 28 | null | transformers | 7,398 | ---
license: apache-2.0
tags:
- image-classification
- pytorch
- onnx
datasets:
- pyronear/openfire
---
# MobileNet V3 - Small model
Pretrained on a dataset for wildfire binary classification (soon to be shared). The MobileNet V3 architecture was introduced in [this paper](https://arxiv.org/pdf/1905.02244.pdf).
##... |
mhdr78/finetuned_parsinlu_en_fa | 7973562fac07b2b0f3370fc23ee842978af773a3 | 2022-07-15T05:16:22.000Z | [
"pytorch",
"tensorboard",
"mt5",
"text2text-generation",
"transformers",
"generated_from_trainer",
"license:cc-by-nc-sa-4.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | mhdr78 | null | mhdr78/finetuned_parsinlu_en_fa | 28 | 1 | transformers | 7,399 | ---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: finetuned_parsinlu_en_fa
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comme... |
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