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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
nateraw/hot-dog | dc768435246614205e59fcd0412937c6bb116083 | 2021-07-01T05:31:18.000Z | [
"pytorch",
"detr",
"object-detection",
"transformers"
] | object-detection | false | nateraw | null | nateraw/hot-dog | 18 | null | transformers | 8,800 | ---
tags:
- object-detection
- pytorch
---
# hot-dog
Ignore me...I'm broken. |
neuropark/sahajBERT-NER | 126f3f6642ea9056fbc3901e6720827ff03a51e1 | 2021-06-15T08:12:18.000Z | [
"pytorch",
"albert",
"token-classification",
"bn",
"dataset:xtreme",
"transformers",
"collaborative",
"bengali",
"NER",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | false | neuropark | null | neuropark/sahajBERT-NER | 18 | 2 | transformers | 8,801 |
---
language: bn
tags:
- collaborative
- bengali
- NER
license: apache-2.0
datasets: xtreme
metrics:
- Loss
- Accuracy
- Precision
- Recall
---
# sahajBERT Named Entity Recognition
## Model description
[sahajBERT](https://huggingface.co/neuropark/sahajBERT-NER) fine-tuned for NER using the bengali split of [WikiAN... |
nielsr/convnext-xlarge-224-22k-1k | 98e544a4f7a730d24dd472bd9ecf87f0694ca72e | 2022-02-22T12:35:38.000Z | [
"pytorch",
"convnext",
"image-classification",
"transformers"
] | image-classification | false | nielsr | null | nielsr/convnext-xlarge-224-22k-1k | 18 | null | transformers | 8,802 | Entry not found |
nntadotzip/xlnet-base-cased-IUChatbot-ontologyDts-BertPretrainedTokenizerFast | 516f02edce4a408d4b46fe90b9c9e226cba842a0 | 2022-01-20T18:06:05.000Z | [
"pytorch",
"tensorboard",
"xlnet",
"question-answering",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | question-answering | false | nntadotzip | null | nntadotzip/xlnet-base-cased-IUChatbot-ontologyDts-BertPretrainedTokenizerFast | 18 | null | transformers | 8,803 | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: xlnet-base-cased-IUChatbot-ontologyDts-BertPretrainedTokenizerFast
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then rem... |
nyu-mll/roberta-med-small-1M-2 | d57b4ce9b7d78f0980fcb2d43b2a272677871318 | 2021-05-20T19:07:56.000Z | [
"pytorch",
"jax",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | nyu-mll | null | nyu-mll/roberta-med-small-1M-2 | 18 | null | transformers | 8,804 | # RoBERTa Pretrained on Smaller Datasets
We pretrain RoBERTa on smaller datasets (1M, 10M, 100M, 1B tokens). We release 3 models with lowest perplexities for each pretraining data size out of 25 runs (or 10 in the case of 1B tokens). The pretraining data reproduces that of BERT: We combine English Wikipedia and a repr... |
patrickvonplaten/reformer-tiny-random | b28e78c699eb382c5c533475a87f64f26394513b | 2021-05-20T02:18:13.000Z | [
"pytorch",
"bert",
"text-generation",
"transformers"
] | text-generation | false | patrickvonplaten | null | patrickvonplaten/reformer-tiny-random | 18 | null | transformers | 8,805 | Entry not found |
pere/norwegian-gpt2-vgd | a4e18964aa637471296c11a09b6491c5ebe009d2 | 2021-11-02T21:15:41.000Z | [
"pytorch",
"jax",
"tensorboard",
"gpt2",
"text-generation",
"no",
"transformers",
"norwegian",
"GPT2",
"casual language modeling",
"license:cc-by-4.0"
] | text-generation | false | pere | null | pere/norwegian-gpt2-vgd | 18 | null | transformers | 8,806 | ---
language: no
license: cc-by-4.0
tags:
- norwegian
- GPT2
- casual language modeling
---
# Norwegian GPT-2 - Social
## Description
Private test of gpt fine-tuning based on vgd.
The following sub-corpora are used for the base model:
```bash
wikipedia_download_nb.jsonl
wikipedia_download_nn.jsonl
newspapers_online_... |
pertschuk/albert-base-quora-classifier | 052bb0476fc6840b5e8ac59461e2709644597b61 | 2020-04-24T16:04:59.000Z | [
"pytorch",
"albert",
"text-classification",
"transformers"
] | text-classification | false | pertschuk | null | pertschuk/albert-base-quora-classifier | 18 | null | transformers | 8,807 | Entry not found |
philippelaban/summary_loop10 | 651e90be5498581fc2532b1a4cab085525e374aa | 2022-02-09T22:02:12.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"dataset:cnn_dailymail",
"transformers",
"summarization",
"license:apache-2.0"
] | summarization | false | philippelaban | null | philippelaban/summary_loop10 | 18 | 2 | transformers | 8,808 | ---
language:
- en
tags:
- summarization
license: apache-2.0
datasets:
- cnn_dailymail
---
# Try out in the Hosted inference API
In the right panel, you can try to the model (although it only handles a short sequence length).
Enter the document you want to summarize in the panel on the right.
# Model ... |
philschmid/mt5-small-prompted-germanquad-1 | 7e4252389899b17fb8d4659d9784c6c8ab506297 | 2021-12-24T11:10:03.000Z | [
"pytorch",
"tensorboard",
"mt5",
"text2text-generation",
"dataset:philschmid/prompted-germanquad",
"transformers",
"summarization",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | summarization | false | philschmid | null | philschmid/mt5-small-prompted-germanquad-1 | 18 | null | transformers | 8,809 | ---
license: apache-2.0
tags:
- summarization
datasets:
- philschmid/prompted-germanquad
widget:
- text: |
Philipp ist 26 Jahre alt und lebt in Nürnberg, Deutschland. Derzeit arbeitet er als Machine Learning Engineer und Tech Lead bei Hugging Face, um künstliche Intelligenz durch Open Source und Open Science zu d... |
pinecone/mpnet-retriever-squad2 | cac1e06fed72fb1f81c9828d4eeb8a16621d7ebf | 2022-01-03T02:42:15.000Z | [
"pytorch",
"mpnet",
"feature-extraction",
"sentence-transformers",
"sentence-similarity",
"transformers"
] | sentence-similarity | false | pinecone | null | pinecone/mpnet-retriever-squad2 | 18 | 2 | sentence-transformers | 8,810 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# {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 cluster... |
prajwalcr/poetry-surprise_gpt2 | 944d9ca68c75383097a8535fbe77519a6dcbe9b7 | 2021-08-03T10:04:51.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | prajwalcr | null | prajwalcr/poetry-surprise_gpt2 | 18 | null | transformers | 8,811 | Entry not found |
pucpr/biobertpt-bio | f02ec2f9c1687aa236c0e23fb00d452d0aacda76 | 2021-10-13T09:27:44.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"pt",
"dataset:biomedical literature from Scielo and Pubmed",
"transformers",
"autotrain_compatible"
] | fill-mask | false | pucpr | null | pucpr/biobertpt-bio | 18 | 4 | transformers | 8,812 | ---
language: "pt"
widget:
- text: "O principal [MASK] da COVID-19 é tosse seca."
- text: "O vírus da gripe apresenta um [MASK] constituído por segmentos de ácido ribonucleico."
datasets:
- biomedical literature from Scielo and Pubmed
thumbnail: "https://raw.githubusercontent.com/HAILab-PUCPR/BioBERTpt/master/images/... |
raynardj/roberta-pubmed | 58d63994a9357d5d2651fec4cab6804dbe9580be | 2021-10-08T02:58:27.000Z | [
"pytorch",
"roberta",
"fill-mask",
"en",
"dataset:pubmed",
"transformers",
"pubmed",
"cancer",
"gene",
"clinical trial",
"bioinformatic",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | raynardj | null | raynardj/roberta-pubmed | 18 | 1 | transformers | 8,813 | ---
language:
- en
tags:
- pubmed
- cancer
- gene
- clinical trial
- bioinformatic
license: apache-2.0
datasets:
- pubmed
widget:
- text: "The <mask> effects of hyperatomarin"
---
# Roberta-Base fine-tuned on [PubMed](https://pubmed.ncbi.nlm.nih.gov/) Abstract
> We limit the training textual data to the following [MeS... |
salesken/content_generation_from_phrases | cc3700cab3cf3a99076f95b606574f96e59e2722 | 2021-05-23T12:23:54.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers",
"salesken",
"license:apache-2.0"
] | text-generation | false | salesken | null | salesken/content_generation_from_phrases | 18 | null | transformers | 8,814 |
---
tags: salesken
license: apache-2.0
inference: false
---
We attempted an entailment-encouraging text generation model to generate content , given a short phrase .
Some the generated sentences like below, for the phrase "data science beginner", really got us excited about the potential applications:
<b> ['Where... |
textattack/roberta-base-WNLI | fcf1b6036509b5b0b43116873e3ba4b1da56a74e | 2021-05-20T22:13:50.000Z | [
"pytorch",
"jax",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | textattack | null | textattack/roberta-base-WNLI | 18 | null | transformers | 8,815 | ## TextAttack Model Card
This `roberta-base` model was fine-tuned for sequence classification using TextAttack
and the glue dataset loaded using the `nlp` library. The model was fine-tuned
for 5 epochs with a batch size of 16, a learning
rate of 5e-05, and a maximum sequence length of 256.
Since this was a classifi... |
textattack/xlnet-large-cased-CoLA | 4fb7b9627f837f36170be6fa8f37b5f95dcac9b0 | 2020-06-09T16:57:33.000Z | [
"pytorch",
"xlnet",
"text-classification",
"transformers"
] | text-classification | false | textattack | null | textattack/xlnet-large-cased-CoLA | 18 | null | transformers | 8,816 | Entry not found |
textattack/xlnet-large-cased-STS-B | 6d0282faa6cc66440a1dabc1111526d242a1c4c0 | 2020-06-09T16:59:30.000Z | [
"pytorch",
"xlnet",
"text-classification",
"transformers"
] | text-classification | false | textattack | null | textattack/xlnet-large-cased-STS-B | 18 | null | transformers | 8,817 | Entry not found |
tiennvcs/layoutlmv2-large-uncased-finetuned-infovqa | c2c1495c9e4e4963eaa8e95c303a9770ed6f6687 | 2021-11-09T13:42:04.000Z | [
"pytorch",
"tensorboard",
"layoutlmv2",
"question-answering",
"transformers",
"generated_from_trainer",
"license:cc-by-nc-sa-4.0",
"model-index",
"autotrain_compatible"
] | question-answering | false | tiennvcs | null | tiennvcs/layoutlmv2-large-uncased-finetuned-infovqa | 18 | 1 | transformers | 8,818 | ---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
model-index:
- name: layoutlmv2-large-uncased-finetuned-infovqa
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 com... |
tli8hf/unqover-bert-base-uncased-newsqa | c479a1b05c710946148a24e0373d7602a9cff824 | 2021-05-20T07:53:24.000Z | [
"pytorch",
"jax",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | tli8hf | null | tli8hf/unqover-bert-base-uncased-newsqa | 18 | null | transformers | 8,819 | Entry not found |
trig/multiverse | b555c783b0abddfe3c2df713022a2c4348a006bf | 2021-08-29T18:05:47.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | trig | null | trig/multiverse | 18 | null | transformers | 8,820 | ---
tags:
- conversational
---
# chatbot using multiple shows |
tyqiangz/indobert-lite-large-p2-smsa | e1ca516d9e58ba32ebbf6164f928abca78e4974b | 2021-10-06T17:12:46.000Z | [
"pytorch",
"albert",
"text-classification",
"id",
"dataset:Indo4B",
"arxiv:2009.05387",
"transformers",
"indobert",
"indobenchmark",
"indonlu",
"license:mit"
] | text-classification | false | tyqiangz | null | tyqiangz/indobert-lite-large-p2-smsa | 18 | 1 | transformers | 8,821 | ---
language: id
tags:
- indobert
- indobenchmark
- indonlu
license: mit
inference: true
datasets:
- Indo4B
---
# IndoBERT-Lite Large Model (phase2 - uncased) Finetuned on IndoNLU SmSA dataset
Finetuned the IndoBERT-Lite Large Model (phase2 - uncased) model on the IndoNLU SmSA dataset following ... |
uclanlp/plbart-multi_task-strong | b958e874bf2ab98f2f62ce449e3a13013605580c | 2022-03-02T07:42:23.000Z | [
"pytorch",
"plbart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | uclanlp | null | uclanlp/plbart-multi_task-strong | 18 | null | transformers | 8,822 | Entry not found |
vasudevgupta/mbart-summarizer-interiit | 8e2bfd5ac2e731bd0d1274735c9bfbaa62c0a86a | 2021-03-28T17:49:15.000Z | [
"pytorch",
"mbart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | vasudevgupta | null | vasudevgupta/mbart-summarizer-interiit | 18 | null | transformers | 8,823 | This model is trained as a part of **InterIIT'21 competition**, on the dataset provided by Bridgei2i. It is able to do multilingual (Hindi, English, Hinglish) summarization (many -> one) & is capable of generating summaries in English regardless of the input language.
| Rouge-L | Sacrebleu | Headline Sim... |
vishnun/bert-base-cased-tamil-mix-sentiment | 940036b33e6732512ee1474a3a5eb5c1aca02aee | 2021-08-14T09:51:56.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | vishnun | null | vishnun/bert-base-cased-tamil-mix-sentiment | 18 | null | transformers | 8,824 | # Tamil Mix Sentiment analysis
Model is trained on tamil-mix-sentiment dataset and finetuned with backend as bert-base-cased model
## Inference usage
On the hosted Inference type in the text for which you want to classify.
Eg: Super a iruku bro intha work, vera level mass |
vwoloszyn/gtp2-email | 7218e48862ce6fed78e94f41195a32ea494fe12c | 2022-02-08T00:24:59.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | vwoloszyn | null | vwoloszyn/gtp2-email | 18 | null | transformers | 8,825 | Entry not found |
w11wo/indo-roberta-small | 9cb35a1ae4b311b4fc09348c2f84ceda5fe47605 | 2021-05-20T23:08:29.000Z | [
"pytorch",
"tf",
"jax",
"roberta",
"fill-mask",
"id",
"dataset:wikipedia",
"arxiv:1907.11692",
"transformers",
"indo-roberta-small",
"license:mit",
"autotrain_compatible"
] | fill-mask | false | w11wo | null | w11wo/indo-roberta-small | 18 | null | transformers | 8,826 | ---
language: id
tags:
- indo-roberta-small
license: mit
datasets:
- wikipedia
widget:
- text: "Karena pandemi ini, kita harus <mask> di rumah saja."
---
## Indo RoBERTa Small
Indo RoBERTa Small is a masked language model based on the [RoBERTa model](https://arxiv.org/abs/1907.11692). It was trained on the latest (lat... |
wietsedv/bert-base-dutch-cased-finetuned-conll2002-ner | c49a532d3ae3a22509e769e5f3fd045a577856fc | 2021-05-20T09:07:16.000Z | [
"pytorch",
"jax",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | wietsedv | null | wietsedv/bert-base-dutch-cased-finetuned-conll2002-ner | 18 | null | transformers | 8,827 | Entry not found |
yhavinga/t5-v1.1-large-dutch-cnn-test | 537a589a88f69a43f55ba0bf43ae09ea4cc6a559 | 2022-01-16T13:26:39.000Z | [
"pytorch",
"jax",
"tensorboard",
"t5",
"text2text-generation",
"nl",
"dataset:yhavinga/mc4_nl_cleaned",
"dataset:ml6team/cnn_dailymail_nl",
"transformers",
"seq2seq",
"lm-head",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | yhavinga | null | yhavinga/t5-v1.1-large-dutch-cnn-test | 18 | null | transformers | 8,828 | ---
language:
- nl
datasets:
- yhavinga/mc4_nl_cleaned
- ml6team/cnn_dailymail_nl
tags:
- seq2seq
- lm-head
license: apache-2.0
inference: false
---
# T5 v1.1 Large finetuned for CNN news summarization in Dutch 🇳🇱
This model is [t5-v1.1-large-dutch-cased](https://huggingface.co/yhavinga/t5-v1.1-large-dutch-cased) f... |
youzanai/bert-shipping-address-chinese | d6c470ee787ed9cb95f20c535e214d4977a30b12 | 2022-03-21T02:43:54.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | youzanai | null | youzanai/bert-shipping-address-chinese | 18 | null | transformers | 8,829 | ---
license: apache-2.0
---
基于有赞客户收货地址语料训练的bert模型。
模型示例代码参考 https://github.com/youzanai/trexpark |
Davlan/xlm-roberta-base-finetuned-zulu | d6750eceb456ed59716e82cb9f988cd22b1d62a8 | 2022-02-25T14:50:25.000Z | [
"pytorch",
"xlm-roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | Davlan | null | Davlan/xlm-roberta-base-finetuned-zulu | 18 | null | transformers | 8,830 | Entry not found |
cnicu/pegasus-large-booksum | f3238accc4b91cd60ba7595c1757fc82707de2ff | 2022-02-28T12:12:37.000Z | [
"pytorch",
"pegasus",
"text2text-generation",
"dataset:kmfoda/booksum",
"transformers",
"summarization",
"license:mit",
"autotrain_compatible"
] | summarization | false | cnicu | null | cnicu/pegasus-large-booksum | 18 | null | transformers | 8,831 | ---
license: mit
tags:
- summarization
datasets:
- kmfoda/booksum
---
|
ghadeermobasher/Model_org_2 | 871cf28d066b36524a0eec5828939633409974af | 2022-03-02T10:06:47.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/Model_org_2 | 18 | null | transformers | 8,832 | Entry not found |
davanstrien/flyswot_test | adcf0d50a8b79ab90ca5ac72f80b11e133c19bb1 | 2022-03-01T18:06:33.000Z | [
"pytorch",
"convnext",
"image-classification",
"dataset:image_folder",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | image-classification | false | davanstrien | null | davanstrien/flyswot_test | 18 | null | transformers | 8,833 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- image_folder
model-index:
- name: flyswot_test
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
... |
abdelhalim/Shower_Sound_Recognition | 9da22aa51599aad82ff6082fb1f84d230e38a029 | 2022-03-03T22:09:48.000Z | [
"pytorch",
"wav2vec2",
"audio-classification",
"dataset:SHD-2",
"transformers",
"audio",
"audio-classificaiton",
"shower detection"
] | audio-classification | false | abdelhalim | null | abdelhalim/Shower_Sound_Recognition | 18 | null | transformers | 8,834 | ---
datasets:
- SHD-2
tags:
- audio
- audio-classificaiton
- shower detection
metrics:
- Accuracy
---
**Context**
Most of our great brilliant ideas happen in periods of relaxation, like taking a
shower, however, once we leave the shower, we forget the brilliant idea. What if
we do not forget, and collect your ideas... |
drAbreu/bioBERT-NER-BC2GM_corpus | 99d3d7708b2b57d733a31fcb4347abc237c06a18 | 2022-03-15T14:44:33.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"dataset:bc2gm_corpus",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | token-classification | false | drAbreu | null | drAbreu/bioBERT-NER-BC2GM_corpus | 18 | null | transformers | 8,835 | ---
tags:
- generated_from_trainer
datasets:
- bc2gm_corpus
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bioBERT-finrtuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: bc2gm_corpus
type: bc2gm_corpus
args: bc2gm_cor... |
ndubuisi/pfam_init | 6fb5ba8b9a5291a8f4af05b050146671d2c31cc2 | 2022-03-09T06:20:17.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | ndubuisi | null | ndubuisi/pfam_init | 18 | null | transformers | 8,836 | Entry not found |
ctu-aic/xlm-roberta-large-xnli-csfever | 9221e9e7a6a57f5e3d8fe20d1bcf4fa304f2c113 | 2022-03-11T12:30:17.000Z | [
"pytorch",
"xlm-roberta",
"text-classification",
"transformers",
"license:cc-by-sa-3.0"
] | text-classification | false | ctu-aic | null | ctu-aic/xlm-roberta-large-xnli-csfever | 18 | 1 | transformers | 8,837 | ---
license: cc-by-sa-3.0
---
|
simonschoe/TransformationTransformer | 9acedf888cc699f04a35f1772cefb5facae3185d | 2022-07-28T15:04:47.000Z | [
"pytorch",
"roberta",
"text-classification",
"en",
"transformers"
] | text-classification | false | simonschoe | null | simonschoe/TransformationTransformer | 18 | null | transformers | 8,838 | ---
language:
- en
pipeline_tag: text-classification
tags:
widget:
- text: "And it was great to see how our Chinese team very much aware of that and of shifting all the resourcing to really tap into these opportunities."
example_title: "Examplary Transformation Sentence"
- text: "But we will continue to recruit even ... |
wanyu/IteraTeR-PEGASUS-Revision-Generator | 3e88c310f0f5d702bd1ba50e89eb07055d76f293 | 2022-04-04T20:08:12.000Z | [
"pytorch",
"pegasus",
"text2text-generation",
"dataset:IteraTeR_full_sent",
"arxiv:2203.03802",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | wanyu | null | wanyu/IteraTeR-PEGASUS-Revision-Generator | 18 | null | transformers | 8,839 | ---
datasets:
- IteraTeR_full_sent
---
# IteraTeR PEGASUS model
This model was obtained by fine-tuning [google/pegasus-large](https://huggingface.co/google/pegasus-large) on [IteraTeR-full-sent](https://huggingface.co/datasets/wanyu/IteraTeR_full_sent) dataset.
Paper: [Understanding Iterative Revision from Human-Writ... |
Helsinki-NLP/opus-mt-tc-big-en-fi | 160f657ed4985485d6e87b746a86e4382f67ef47 | 2022-06-01T13:10:26.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"fi",
"transformers",
"translation",
"opus-mt-tc",
"license:cc-by-4.0",
"model-index",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-tc-big-en-fi | 18 | null | transformers | 8,840 | ---
language:
- en
- fi
tags:
- translation
- opus-mt-tc
license: cc-by-4.0
model-index:
- name: opus-mt-tc-big-en-fi
results:
- task:
name: Translation eng-fin
type: translation
args: eng-fin
dataset:
name: flores101-devtest
type: flores_101
args: eng fin devtest
metrics... |
efederici/sentence-it5-base | 73d3d9a749d4fbe85c54e501b334f9000a7f43cb | 2022-03-29T23:09:01.000Z | [
"pytorch",
"t5",
"it",
"sentence-transformers",
"feature-extraction",
"sentence-similarity",
"transformers"
] | sentence-similarity | false | efederici | null | efederici/sentence-it5-base | 18 | 2 | sentence-transformers | 8,841 | ---
pipeline_tag: sentence-similarity
language:
- it
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# sentence-IT5-base
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 512 dimensional dense vector space and can be used... |
morenolq/spotify-podcast-advertising-classification | 43e9bd006f0d401e5161434856a48a19c58bebbc | 2022-07-02T12:12:18.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"dataset:Spotify Podcasts Dataset",
"transformers",
"classification"
] | text-classification | false | morenolq | null | morenolq/spotify-podcast-advertising-classification | 18 | 2 | transformers | 8,842 | ---
language: "en"
datasets:
- Spotify Podcasts Dataset
tags:
- bert
- classification
- pytorch
pipeline:
- text-classification
widget:
- text: "__START__ [SEP] This is the first podcast on natural language processing applied to spoken language."
- text: "This is the first podcast on natural language processing applied... |
AnonymousSub/roberta_FT_new_newsqa | 226a14e7e40e5141b3bcf6a7f94b216645990755 | 2022-04-05T15:12:55.000Z | [
"pytorch",
"roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | AnonymousSub | null | AnonymousSub/roberta_FT_new_newsqa | 18 | null | transformers | 8,843 | Entry not found |
vachevkd/qna-t5base-squad | 71d22699f1562d48d6841577be0d0dc656249162 | 2022-04-06T18:23:29.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | vachevkd | null | vachevkd/qna-t5base-squad | 18 | null | transformers | 8,844 | Entry not found |
vachevkd/dg-t5base-race | be3fe37c79b377c9616735013c04859012fbbfe0 | 2022-04-06T18:30:17.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | vachevkd | null | vachevkd/dg-t5base-race | 18 | null | transformers | 8,845 | Entry not found |
ydshieh/tiny-random-gptj-for-causal-lm | f64f714d1334967753f62f401bb54e6aa8577e1d | 2022-04-08T10:20:49.000Z | [
"pytorch",
"tf",
"gptj",
"text-generation",
"transformers"
] | text-generation | false | ydshieh | null | ydshieh/tiny-random-gptj-for-causal-lm | 18 | null | transformers | 8,846 | Entry not found |
agdsga/chinese-pert-large-finetuned-product | b838e495b16be9d00b976d5e688aed12a27d9c73 | 2022-04-12T11:42:30.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-generation",
"transformers",
"generated_from_trainer",
"license:cc-by-nc-sa-4.0",
"model-index"
] | text-generation | false | agdsga | null | agdsga/chinese-pert-large-finetuned-product | 18 | null | transformers | 8,847 | ---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
model-index:
- name: chinese-pert-large-finetuned-product
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/convnext-tiny-224-finetuned-eurosat-albumentations | 5aac61b2ae3092a51c276a26fa85dbc2ef29dd70 | 2022-04-12T12:40:48.000Z | [
"pytorch",
"tensorboard",
"convnext",
"image-classification",
"dataset:image_folder",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | image-classification | false | nielsr | null | nielsr/convnext-tiny-224-finetuned-eurosat-albumentations | 18 | null | transformers | 8,848 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- accuracy
model-index:
- name: convnext-tiny-224-finetuned-eurosat-albumentations
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: image_folder
type: image_folde... |
Wanjiru/bert-base-multilingual_en_ner_ | 40da7ea7287bf8b404b27dd86e55285513008be6 | 2022-04-14T12:33:55.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | Wanjiru | null | Wanjiru/bert-base-multilingual_en_ner_ | 18 | 1 | transformers | 8,849 | Label ID Label Name
0 0
1. B-PER
2. I-PER
3. B-ORG
4. I-ORG
5. B-LOC
6. I-LOC |
rmihaylov/bert-base-ner-theseus-bg | 7a790473402b50e72e29f9b65099ce397de7ac7b | 2022-04-16T19:43:53.000Z | [
"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-ner-theseus-bg | 18 | null | transformers | 8,850 | ---
inference: false
language:
- bg
license: mit
datasets:
- oscar
- chitanka
- wikipedia
tags:
- torch
---
# BERT BASE (cased) finetuned on Bulgarian named-entity-recognition data
Pretrained model on Bulgarian language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.... |
Souvikcmsa/Roberta_Sentiment_Analysis | e3cf03e5e9636fbcee84e97ab89a74f20f2ef773 | 2022-04-20T08:53:33.000Z | [
"pytorch",
"roberta",
"text-classification",
"en",
"dataset:Souvikcmsa/autotrain-data-sentimentAnalysis_By_Souvik",
"transformers",
"autotrain",
"co2_eq_emissions"
] | text-classification | false | Souvikcmsa | null | Souvikcmsa/Roberta_Sentiment_Analysis | 18 | null | transformers | 8,851 | ---
tags: autotrain
language: en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- Souvikcmsa/autotrain-data-sentimentAnalysis_By_Souvik
co2_eq_emissions: 4.453029772491864
---
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 762623422
- CO2 Emissions (in grams): 4.45302977249186... |
Zia/distilbert-base-uncased-finetuned-emotion | 57931d0b1cedcdf6373f68c78bdcf24522d6f6d5 | 2022-04-24T17:48:51.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | Zia | null | Zia/distilbert-base-uncased-finetuned-emotion | 18 | null | transformers | 8,852 | ---
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... |
yhavinga/t5-small-24L-ccmatrix-multi | b9a8c9c56920570a39de96831255c91ece6c8a40 | 2022-06-14T10:29:41.000Z | [
"pytorch",
"jax",
"tensorboard",
"t5",
"text2text-generation",
"nl",
"en",
"dataset:yhavinga/mc4_nl_cleaned",
"dataset:yhavinga/ccmatrix",
"transformers",
"translation",
"seq2seq",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | yhavinga | null | yhavinga/t5-small-24L-ccmatrix-multi | 18 | null | transformers | 8,853 | ---
language:
- nl
- en
datasets:
- yhavinga/mc4_nl_cleaned
- yhavinga/ccmatrix
tags:
- t5
- translation
- seq2seq
pipeline_tag: translation
widget:
- text: "It is a painful and tragic spectacle that rises before me: I have drawn back the curtain from the rottenness of man. This word, in my mouth, is at least free fro... |
davidenam/distilbert-base-uncased-finetuned-emotion | 888eea940289f187a159db2ff86742f9e97203bc | 2022-04-27T21:59:00.000Z | [
"pytorch",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | davidenam | null | davidenam/distilbert-base-uncased-finetuned-emotion | 18 | null | transformers | 8,854 | ---
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... |
OFA-Sys/OFA-medium | 0f35145e94917f4954001fb8ac213dd626de1e72 | 2022-07-25T11:50:59.000Z | [
"pytorch",
"ofa",
"transformers",
"license:apache-2.0"
] | null | false | OFA-Sys | null | OFA-Sys/OFA-medium | 18 | 3 | transformers | 8,855 | ---
license: apache-2.0
---
# OFA-medium
This is the **medium** version of OFA pretrained model. OFA is a unified multimodal pretrained model that unifies modalities (i.e., cross-modality, vision, language) and tasks (e.g., image generation, visual grounding, image captioning, image classification, text generation, et... |
Truefilter/bbase_go_emotions | 0a80b3900c5344f15f02bbfff149ad8751b3a4f3 | 2022-04-29T15:31:45.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | Truefilter | null | Truefilter/bbase_go_emotions | 18 | null | transformers | 8,856 | Entry not found |
anshr/distilgpt2_supervised_model_final | a900c56c19bb7915f875bde78759c8e3718bfff8 | 2022-05-02T22:15:49.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | anshr | null | anshr/distilgpt2_supervised_model_final | 18 | null | transformers | 8,857 | Entry not found |
enimai/mbart-large-50-paraphrase-finetuned-for-fr | dea9e2d720c1c1841a19b1d30262ca061a532219 | 2022-05-03T17:36:09.000Z | [
"pytorch",
"mbart",
"text2text-generation",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | enimai | null | enimai/mbart-large-50-paraphrase-finetuned-for-fr | 18 | null | transformers | 8,858 | ---
license: apache-2.0
---
|
jeremyccollinsmpi/autotrain-inference_probability_2-840226804 | 0f58601ed0d3f53339cfffd5f8551a554c2494f8 | 2022-05-17T07:41:46.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"dataset:jeremyccollinsmpi/autotrain-data-inference_probability_2",
"transformers",
"autotrain",
"co2_eq_emissions",
"autotrain_compatible"
] | text2text-generation | false | jeremyccollinsmpi | null | jeremyccollinsmpi/autotrain-inference_probability_2-840226804 | 18 | null | transformers | 8,859 |
---
tags: autotrain
language: en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- jeremyccollinsmpi/autotrain-data-inference_probability_2
co2_eq_emissions: 0.02920886926438328
---
# Description
The input structure is:
summarize: [text]. hypothesis: [hypothesis] , and the output is 0 (hypothesis is not supporte... |
dpuccine/bert-finetuned-ner | c3c12a639d0f92c8385161f48d0a56cf6c007ff0 | 2022-05-10T17:29:20.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"dataset:conll2003",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | dpuccine | null | dpuccine/bert-finetuned-ner | 18 | null | transformers | 8,860 | ---
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... |
CEBaB/lstm.CEBaB.sa.3-class.exclusive.seed_77 | acb48ae7cda063c5e2c789afb64767aaacc51814 | 2022-05-11T01:22:11.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | CEBaB | null | CEBaB/lstm.CEBaB.sa.3-class.exclusive.seed_77 | 18 | null | transformers | 8,861 | Entry not found |
CEBaB/lstm.CEBaB.sa.5-class.exclusive.seed_77 | 8804ed8fea1fad03270c0ce8ed3cda9d3af8da9b | 2022-05-11T01:39:26.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | CEBaB | null | CEBaB/lstm.CEBaB.sa.5-class.exclusive.seed_77 | 18 | null | transformers | 8,862 | Entry not found |
James-kc-min/F_Roberta_classifier2 | ffda557d70a9139a57f8aeb44d08eea669de586c | 2022-05-11T14:15:01.000Z | [
"pytorch",
"tensorboard",
"roberta",
"text-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | James-kc-min | null | James-kc-min/F_Roberta_classifier2 | 18 | null | transformers | 8,863 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: F_Roberta_classifier2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, ... |
edumunozsala/bertin_base_sentiment_analysis_es | 159a628aa01ee6d5930752ac632de7327ab3fa38 | 2022-07-29T09:18:17.000Z | [
"pytorch",
"roberta",
"text-classification",
"es",
"dataset:IMDbreviews_es",
"transformers",
"sagemaker",
"bertin",
"TextClassification",
"SentimentAnalysis",
"license:apache-2.0",
"model-index"
] | text-classification | false | edumunozsala | null | edumunozsala/bertin_base_sentiment_analysis_es | 18 | null | transformers | 8,864 | ---
language: es
tags:
- sagemaker
- bertin
- TextClassification
- SentimentAnalysis
license: apache-2.0
datasets:
- IMDbreviews_es
metrics:
- accuracy
model-index:
- name: bertin_base_sentiment_analysis_es
results:
- task:
name: Sentiment Analysis
type: sentiment-analysis
dataset:
name:... |
xhyi/CodeGen-2B-Multi | bf4b5c321dd655e9714fe284bf07c2be01fd93aa | 2022-05-18T17:33:15.000Z | [
"pytorch",
"codegen",
"text-generation",
"en",
"transformers",
"text generation",
"causal-lm",
"license:bsd-3-clause"
] | text-generation | false | xhyi | null | xhyi/CodeGen-2B-Multi | 18 | null | transformers | 8,865 | ---
language:
- en
tags:
- codegen
- text generation
- pytorch
- causal-lm
license: bsd-3-clause
---
# Salesforce CodeGen
ported salesforce codegen models to work on huggingface transformers without any extra code (the model specific code is bundled)
## Overview
The CodeGen model was proposed in by Erik Nijkamp, Bo... |
steysie/paraphrase-multilingual-mpnet-base-v2-tuned-smartcat | 35dce5fafed492a692d9bd072d7953a5d7fdfc00 | 2022-05-20T20:10:09.000Z | [
"pytorch",
"xlm-roberta",
"text-generation",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-generation | false | steysie | null | steysie/paraphrase-multilingual-mpnet-base-v2-tuned-smartcat | 18 | null | transformers | 8,866 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: paraphrase-multilingual-mpnet-base-v2-tuned-smartcat
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 thi... |
imohammad12/GRS-Grammar-Checker-DeBerta | 5dd540d9a686c056e6c8e520a34ccdc929a547da | 2022-05-26T10:48:39.000Z | [
"pytorch",
"deberta",
"text-classification",
"en",
"transformers",
"grs"
] | text-classification | false | imohammad12 | null | imohammad12/GRS-Grammar-Checker-DeBerta | 18 | null | transformers | 8,867 | ---
language: en
tags: grs
---
## Citation
Please star the [GRS GitHub repo](https://github.com/imohammad12/GRS) and cite the paper if you found our model useful:
```
@inproceedings{dehghan-etal-2022-grs,
title = "{GRS}: Combining Generation and Revision in Unsupervised Sentence Simplification",
author = "Deh... |
gigikenneth/family-guy-bot | d02b801f8d9a48ae1d6342466a41a39a8c501ac0 | 2022-05-26T19:44:29.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | gigikenneth | null | gigikenneth/family-guy-bot | 18 | null | transformers | 8,868 | ---
tags:
- conversational
---
# Stewie Chatbot |
RANG012/SENATOR | 64670b5d0bd1fbdea79a55e29b8ab405e742bd41 | 2022-06-01T07:17:06.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:imdb",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | RANG012 | null | RANG012/SENATOR | 18 | null | transformers | 8,869 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
- f1
model-index:
- name: SENATOR
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
args: plain_text
metrics:
- name: Accuracy
... |
Yarn/distilbert-base-uncased-mnli-finetuned-mnli | f7e6ca9e289817e2de1167156bcd735673af5285 | 2022-06-21T18:16:47.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"transformers"
] | text-classification | false | Yarn | null | Yarn/distilbert-base-uncased-mnli-finetuned-mnli | 18 | null | transformers | 8,870 | Entry not found |
ghadeermobasher/Original-PubMedBERT-NCBI | 6c6f160510ee7ee986cadbfc4cbb59a67a9116fa | 2022-06-09T10:27:10.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/Original-PubMedBERT-NCBI | 18 | null | transformers | 8,871 | Entry not found |
ghadeermobasher/Orignal-SciBERT-NCBI | 8d7878273baad8f4b60ecdd710658730ea91d36e | 2022-06-09T11:24:21.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/Orignal-SciBERT-NCBI | 18 | null | transformers | 8,872 | Entry not found |
ghadeermobasher/Original-BlueBERT-BC5CDR-Disease | 97893864f2f0011b7bb6040d50953a940d068b3f | 2022-06-09T11:20:21.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/Original-BlueBERT-BC5CDR-Disease | 18 | null | transformers | 8,873 | Entry not found |
ghadeermobasher/Original-PubMedBERT-BC5CDR-disease | 9e601891312d968a56cbef491229c3d228953340 | 2022-06-09T11:29:40.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/Original-PubMedBERT-BC5CDR-disease | 18 | null | transformers | 8,874 | Entry not found |
ghadeermobasher/Original-BlueBERT-BC5CDR-Chemical | 821bfe60dc11f695657a253fe401f6f9cebd7d38 | 2022-06-09T12:03:59.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/Original-BlueBERT-BC5CDR-Chemical | 18 | null | transformers | 8,875 | Entry not found |
ghadeermobasher/Original-PubMedBERT-BC5CDR-Chemical | dee786252092c1135c972467ff189207f49e92fc | 2022-06-09T11:55:45.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/Original-PubMedBERT-BC5CDR-Chemical | 18 | null | transformers | 8,876 | Entry not found |
ghadeermobasher/Original-SciBERT-BC4CHEMD-O | d1eda4a4218237ca965a2206d22d24c5bed19a7c | 2022-06-09T14:06:57.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/Original-SciBERT-BC4CHEMD-O | 18 | null | transformers | 8,877 | Entry not found |
ghadeermobasher/Original-PubMedBERT-Linnaeus | 9b32352012d1494fac69ccdab79f37daa4bdb6eb | 2022-06-10T11:13:09.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/Original-PubMedBERT-Linnaeus | 18 | null | transformers | 8,878 | Entry not found |
Anjoe/german-poetry-gpt2-large | 25d1a886fbe54bebb32bd079e22fec42d7397327 | 2022-07-21T14:35:09.000Z | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index"
] | text-generation | false | Anjoe | null | Anjoe/german-poetry-gpt2-large | 18 | null | transformers | 8,879 | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: german-poetry-gpt2-large
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. -->
# german-poetry-gpt... |
speechbrain/asr-wav2vec2-dvoice-amharic | ee19134f21287dd4179087aa230547ebe0ad02fa | 2022-06-10T01:30:20.000Z | [
"wav2vec2",
"feature-extraction",
"dar",
"dataset:Dvoice",
"speechbrain",
"CTC",
"pytorch",
"Transformer",
"license:apache-2.0",
"automatic-speech-recognition"
] | automatic-speech-recognition | false | speechbrain | null | speechbrain/asr-wav2vec2-dvoice-amharic | 18 | 1 | speechbrain | 8,880 | ---
language: "dar"
thumbnail:
pipeline_tag: automatic-speech-recognition
tags:
- CTC
- pytorch
- speechbrain
- Transformer
license: "apache-2.0"
datasets:
- Dvoice
metrics:
- wer
- cer
---
<iframe src="https://ghbtns.com/github-btn.html?user=speechbrain&repo=speechbrain&type=star&count=true&size=large&v=2" frameborde... |
AnyaSchen/rugpt3_pushkin | 109105f776fdec08d9eb7572a97ca6f4d92398e5 | 2022-06-15T11:25:56.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | AnyaSchen | null | AnyaSchen/rugpt3_pushkin | 18 | null | transformers | 8,881 | This model was created by additional training of the giant GPT-3 medium on the works of A.S. Pushkin. Now this model can generate poetry in the style of this poet. Fine-tuning of GPT-3 was produced.
![alt text](https://lh3.googleusercontent.com/73NLTubc1m-Kiz2GJPv44cyMHQgaq32RGr7aWPfsEH5LCpqZxyqtj0TXk6Cw3gjfCzo=w2400... |
rsuwaileh/IDRISI-LMR-HD-TB | 3510abf3da66d8f5529faffdf1c1caf720923985 | 2022-07-18T09:17:42.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | rsuwaileh | null | rsuwaileh/IDRISI-LMR-HD-TB | 18 | null | transformers | 8,882 | This model is a BERT-based Location Mention Recognition model that is adopted from the [TLLMR4CM GitHub](https://github.com/rsuwaileh/TLLMR4CM/).
The model is trained using Hurricane Dorian 2019 event (training, development, and test data are used for training) from [IDRISI-R dataset](https://github.com/rsuwaileh/IDRIS... |
QCRI/bert-base-cased-ccg | 1019a0e7137e1ac936d702b9fd406736870848e2 | 2022-06-13T08:25:22.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"license:cc-by-nc-4.0",
"autotrain_compatible"
] | token-classification | false | QCRI | null | QCRI/bert-base-cased-ccg | 18 | null | transformers | 8,883 | ---
license: cc-by-nc-4.0
---
|
ghadeermobasher/BC4CHEMD-Chem-Modified-BlueBERT-384 | c6ecd2e051542a5f6038ae0fbb4678b892ccef5f | 2022-06-14T18:33:04.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/BC4CHEMD-Chem-Modified-BlueBERT-384 | 18 | null | transformers | 8,884 | Entry not found |
ahmeddbahaa/xlmroberta-finetune-en-cnn | b7b26302a1ad9b37274156df47ba67a328db3c16 | 2022-06-15T15:56:54.000Z | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"summarization",
"en",
"ecnoder-decoder",
"xlmroberta",
"Abstractive Summarization",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | summarization | false | ahmeddbahaa | null | ahmeddbahaa/xlmroberta-finetune-en-cnn | 18 | null | transformers | 8,885 | ---
tags:
- summarization
- en
- ecnoder-decoder
- xlmroberta
- Abstractive Summarization
- generated_from_trainer
datasets:
- cnn_dailymail
model-index:
- name: xlmroberta-finetune-en-cnn
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. Yo... |
Bman/DialoGPT-medium-peppapig | 944854efd38f7fe9d8794c4c84ebbb593e75de90 | 2022-06-16T21:59:19.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | Bman | null | Bman/DialoGPT-medium-peppapig | 18 | 1 | transformers | 8,886 | ---
tags:
- conversational
---
# Peppa Pig DialoGPT Model |
Mahmoud1816Yasser/tmp_trainer | 341e9ce2f8a3d2fe33e69074c9b2ca3f16f00c44 | 2022-06-17T21:10:28.000Z | [
"pytorch",
"wav2vec2",
"audio-classification",
"transformers",
"generated_from_trainer",
"model-index"
] | audio-classification | false | Mahmoud1816Yasser | null | Mahmoud1816Yasser/tmp_trainer | 18 | null | transformers | 8,887 | ---
tags:
- generated_from_trainer
model-index:
- name: tmp_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. -->
# tmp_trainer
This model was trained from sc... |
langfab/distilbert-base-uncased-finetuned-movie-genre | ccccffc13708770efbe757a441061150084eb08f | 2022-06-18T19:02:38.000Z | [
"pytorch",
"distilbert",
"text-classification",
"transformers"
] | text-classification | false | langfab | null | langfab/distilbert-base-uncased-finetuned-movie-genre | 18 | null | transformers | 8,888 | Entry not found |
KoichiYasuoka/roberta-base-japanese-aozora-ud-head | 50f04d6d295a46a5f4797590798fd47f9dbac45b | 2022-07-20T03:52:15.000Z | [
"pytorch",
"roberta",
"question-answering",
"ja",
"dataset:universal_dependencies",
"transformers",
"japanese",
"dependency-parsing",
"license:cc-by-sa-4.0",
"autotrain_compatible"
] | question-answering | false | KoichiYasuoka | null | KoichiYasuoka/roberta-base-japanese-aozora-ud-head | 18 | null | transformers | 8,889 | ---
language:
- "ja"
tags:
- "japanese"
- "question-answering"
- "dependency-parsing"
datasets:
- "universal_dependencies"
license: "cc-by-sa-4.0"
pipeline_tag: "question-answering"
widget:
- text: "国語"
context: "全学年にわたって小学校の国語の教科書に挿し絵が用いられている"
- text: "教科書"
context: "全学年にわたって小学校の国語の教科書に挿し絵が用いられている"
- text: "の"
c... |
Zamachi/bert-base-for-multilabel-sentence-classification | 8b52a934c30c9d325322ab6771f0d04e96117457 | 2022-07-14T12:49:58.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | Zamachi | null | Zamachi/bert-base-for-multilabel-sentence-classification | 18 | null | transformers | 8,890 | Entry not found |
ManqingLiu/distilbert-base-uncased-finetuned-emotion | 6fefcec9c6f2607ff45b73c11ca8803739f14d03 | 2022-06-24T06:04:26.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | ManqingLiu | null | ManqingLiu/distilbert-base-uncased-finetuned-emotion | 18 | null | transformers | 8,891 | ---
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... |
austinmw/distilbert-base-uncased-finetuned-health_facts | aba654497687b32f4ec38ca684b79d277a80fd3d | 2022-06-29T18:15:31.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:health_fact",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | austinmw | null | austinmw/distilbert-base-uncased-finetuned-health_facts | 18 | null | transformers | 8,892 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- health_fact
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-health_facts
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: health_fact
type: health_fact
... |
andreaschandra/distilbert-base-uncased-finetuned-emotion | 2ef3e9ba1e9f63ae2050802469f67e0549376e93 | 2022-07-13T13:16:46.000Z | [
"pytorch",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | andreaschandra | null | andreaschandra/distilbert-base-uncased-finetuned-emotion | 18 | null | transformers | 8,893 | ---
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... |
akhisreelibra/bert-malayalam-pos-tagger | ac3d00c95d7df32d0ead63bd00a7d18a63589554 | 2022-07-05T11:26:20.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | akhisreelibra | null | akhisreelibra/bert-malayalam-pos-tagger | 18 | null | transformers | 8,894 | |
naver/efficient-splade-VI-BT-large-query | 8d4ba56f900620a2ca3efdac9a028473bf703aea | 2022-07-08T13:12:22.000Z | [
"pytorch",
"bert",
"fill-mask",
"en",
"dataset:ms_marco",
"transformers",
"splade",
"query-expansion",
"document-expansion",
"bag-of-words",
"passage-retrieval",
"knowledge-distillation",
"document encoder",
"license:cc-by-nc-sa-4.0",
"autotrain_compatible"
] | fill-mask | false | naver | null | naver/efficient-splade-VI-BT-large-query | 18 | null | transformers | 8,895 | ---
license: cc-by-nc-sa-4.0
language: "en"
tags:
- splade
- query-expansion
- document-expansion
- bag-of-words
- passage-retrieval
- knowledge-distillation
- document encoder
datasets:
- ms_marco
---
## Efficient SPLADE
Efficient SPLADE model for passage retrieval. This architecture uses two distinct models for quer... |
annahaz/xlm-roberta-base-finetuned-misogyny-sexism | 93e1a9ad2ffa4bf7151a0b92d0a6d4287f79dfad | 2022-07-27T14:45:20.000Z | [
"pytorch",
"xlm-roberta",
"text-classification",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index"
] | text-classification | false | annahaz | null | annahaz/xlm-roberta-base-finetuned-misogyny-sexism | 18 | null | transformers | 8,896 | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: xlm-roberta-base-finetuned-misogyny-sexism
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and... |
Shredder/My_model | 0ef65cb9b1d4cb0c44e9f26b451247e082e648c0 | 2022-07-09T10:26:12.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | Shredder | null | Shredder/My_model | 18 | null | transformers | 8,897 | Entry not found |
gary109/ai-light-dance_singing3_ft_wav2vec2-large-xlsr-53-v1 | c8a4dda381aa3bcc92a37ae1b3545d203deb5f35 | 2022-07-19T03:23:28.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"transformers",
"gary109/AI_Light_Dance",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | gary109 | null | gary109/ai-light-dance_singing3_ft_wav2vec2-large-xlsr-53-v1 | 18 | null | transformers | 8,898 | ---
license: apache-2.0
tags:
- automatic-speech-recognition
- gary109/AI_Light_Dance
- generated_from_trainer
model-index:
- name: ai-light-dance_singing3_ft_wav2vec2-large-xlsr-53-v1
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
sh... |
abecode/t5-small-finetuned-xsum | dab35e16d9bfd1b202d003f93a2aaf05280f5100 | 2022-07-09T18:56:13.000Z | [
"pytorch",
"tensorboard",
"t5",
"text2text-generation",
"dataset:xsum",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | abecode | null | abecode/t5-small-finetuned-xsum | 18 | null | transformers | 8,899 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- xsum
metrics:
- rouge
model-index:
- name: t5-small-finetuned-xsum
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: xsum
type: xsum
args: default
metrics:
... |
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