modelId stringlengths 4 81 | tags list | pipeline_tag stringclasses 17
values | config dict | downloads int64 0 59.7M | first_commit timestamp[ns, tz=UTC] | card stringlengths 51 438k | embedding list |
|---|---|---|---|---|---|---|---|
AnonymousSub/rule_based_roberta_twostage_quadruplet_epochs_1_shard_1_squad2.0 | [
"pytorch",
"roberta",
"question-answering",
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"no_re... | 4 | null | ---
thumbnail: https://huggingface.co/front/thumbnails/dialogpt.png
language:
- en
tags:
- conversational
- transformers
datasets:
- GDC
metrics:
- perplexity
license: cc-by-4.0
widget:
- text: "Jag ska fika."
---
## DialoGPT_SV
This is a fine-tuned model of the DialoGPT (medium) on the Swedish Gothenburg Dialogue Co... | [
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"... | 24 | null | ---
thumbnail: https://huggingface.co/front/thumbnails/dialogpt.png
language:
- en
license: cc-by-4.0
tags:
- text classification
- transformers
datasets:
- PCL
metrics:
- F1
inference: false
---
## T5Base-PCL
This is a fine-tuned model of T5 (base) on the patronizing and condenscending language (PCL) dataset by Pérez... | [
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AnonymousSub/rule_based_roberta_twostagequadruplet_hier_epochs_1_shard_1 | [
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tags:
- conversational
---
# Addy DialoGPT Model | [
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AnonymousSub/rule_based_roberta_twostagequadruplet_hier_epochs_1_shard_10 | [
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"no_repeat_ngram_size... | 2 | 2022-01-14T06:41:11Z | ---
tags:
- conversational
---
# Shy DialoGPT Model | [
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AnonymousSub/rule_based_roberta_twostagequadruplet_hier_epochs_1_shard_1_wikiqa | [
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"... | 25 | 2022-01-18T04:02:15Z | ---
tags:
- conversational
---
#Parry Bot DialoGPT Model | [
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AnonymousSub/rule_based_roberta_twostagetriplet_hier_epochs_1_shard_10 | [
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"no_repeat_ngram_size... | 6 | null | ---
tags:
- conversational
---
#KATARA DialoGPT Model | [
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AnonymousSub/rule_based_roberta_twostagetriplet_hier_epochs_1_shard_1_squad2.0 | [
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"transformers",
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"no_re... | 4 | null | ---
tags:
- conversational
---
#SOKKA DialoGPT Model | [
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AnonymousSub/rule_based_roberta_twostagetriplet_hier_epochs_1_shard_1_wikiqa | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | {
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"... | 23 | null | ---
tags:
- conversational
---
# Harry Potter Dialog-GPT Model | [
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AnonymousSub/rule_based_twostagetriplet_epochs_1_shard_1_wikiqa | [
"pytorch",
"bert",
"text-classification",
"transformers"
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"no_rep... | 27 | null | ---
tags:
- text-to-image
- torch
inference: false
datasets:
- laion/laion_100m_vqgan_f8
---
This model is trained collaboratively — it is a part of the NeurIPS 2021 demonstration ["Training Transformers Together"](https://training-transformers-together.github.io/).
The latest model checkpoint will be uploaded to thi... | [
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AnonymousSub/unsup-consert-base | [
"pytorch",
"bert",
"feature-extraction",
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] | feature-extraction | {
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"no_repeat_ngram_size": nul... | 6 | 2021-09-02T03:44:56Z | ---
tags:
- conversational
---
# Discord Model Medium 7 epochs | [
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AnonymousSub/unsup-consert-emanuals | [
"pytorch",
"bert",
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"transformers"
] | feature-extraction | {
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"no_repeat_ngram_size": nul... | 2 | null | # Intent Detection with BERT
This model was trained on the [CLINC150](https://arxiv.org/abs/1909.02027) dataset for customer intent detection. The dataset can be found on the [Hub](https://huggingface.co/datasets/clinc_oos). The model is used in Chapter 8: Making Transformers Efficient in Production in the [NLP with T... | [
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AnonymousSub/unsup-consert-papers-bert | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
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"no_repeat_ngram_size": nul... | 9 | 2021-10-28T13:59:04Z | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: bert-base-uncased-issues-128
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. -->
# bert-b... | [
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0.0... |
AnonymousSub/unsup-consert-papers | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
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"no_repeat_ngram_size": nul... | 2 | 2021-08-11T12:00:29Z | # CodeParrot
This is a small version of the CodeParrot tokenizer trained on the [CodeParrot Python code dataset](https://huggingface.co/datasets/transformersbook/codeparrot). The tokenizer is trained in Chapter 10: Training Transformers from Scratch in the [NLP with Transformers book](https://learning.oreilly.com/libr... | [
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0.0... |
AriakimTaiyo/DialoGPT-small-Rikka | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
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"no_repeat_ngram_size... | 8 | null | # GPT-2 Fine-tuning With Vietnamese Six Eight Poems
## Model description
This is a Vietnamese GPT-2 Six Eight Poet Model which is trained on the 10mb of Six Eight poems dataset, based on the Vietnamese Wiki GPT2 pretrained model (https://huggingface.co/danghuy1999/gpt2-viwiki)
## Purpose
This model was made only for f... | [
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Ashkanmh/bert-base-parsbert-uncased-finetuned | [
"pytorch",
"tensorboard",
"bert",
"fill-mask",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | fill-mask | {
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"no_repeat_ngram_size... | 3 | 2021-09-17T02:02:43Z | # TUNiB-Electra
We release several new versions of the [ELECTRA](https://arxiv.org/abs/2003.10555) model, which we name TUNiB-Electra. There are two motivations. First, all the existing pre-trained Korean encoder models are monolingual, that is, they have knowledge about Korean only. Our bilingual models are based... | [
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Ashl3y/model_name | [] | null | {
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"num_beams... | 0 | null | ---
language:
- th
widget:
- text: "ความรัก"
- text: "อยากรู้"
- text: "ไหนว่า"
---
# Generate Thai Lyrics (แต่งเพลงไทยด้วย GPT-2)
GPT-2 for Thai lyrics generation. We use [GPT-2 base Thai](https://huggingface.co/flax-community/gpt2-base-thai) as a pre-trained model
for [Siamzone lyrics](https://www.siamzone.com/musi... | [
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Augustab/distilbert-base-uncased-finetuned-cola | [] | null | {
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"num_beams... | 0 | null | ---
license: cc-by-sa-4.0
tags:
- generated_from_trainer
datasets:
- te_dx_jp
model-index:
- name: t5-base-TEDxJP-11body-0context
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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Augustvember/WokkaBot99 | [] | null | {
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"num_beams... | 0 | 2021-01-20T14:21:17Z | ---
language: en
license: apache-2.0
datasets:
- openwebtext
---
# DistilRoBERTa base model
Forked from https://huggingface.co/distilroberta-base
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Augustvember/WokkaBotF | [] | null | {
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"num_beams... | 0 | null | ---
language: en
pipeline_tag: zero-shot-classification
tags:
- mobilebert
datasets:
- multi_nli
metrics:
- accuracy
---
# Model Card for MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices
# Model Details
## Model Description
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0.0483... |
Augustvember/wokka4 | [
"conversational"
] | conversational | {
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"num_beams... | 0 | null | ---
license: mit
tags:
- generated_from_trainer
datasets:
- null
model_index:
- name: xlm-roberta-base-finetuned-chaii
results:
- task:
name: Question Answering
type: question-answering
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You... | [
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AyushPJ/ai-club-inductions-21-nlp-distilBERT | [
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... | 8 | null | ---
license: agpl-3.0
tags:
- generated_from_trainer
datasets:
- mim_gold_ner
metrics:
- precision
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- f1
- accuracy
model-index:
- name: XLMR-ENIS-finetuned-ner
results:
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name: Token Classification
type: token-classification
dataset:
name: mim_gold_ner
type: mim_gold_ner
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AyushPJ/ai-club-inductions-21-nlp-roBERTa-base-squad-v2 | [
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"transformers",
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license: apache-2.0
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
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AyushPJ/ai-club-inductions-21-nlp-roBERTa | [
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language: zh
datasets: CLUECorpusSmall
widget:
- text: "中国的首都是[MASK]京"
---
# Chinese ALBERT
## Model description
This is the set of Chinese ALBERT models pre-trained by UER-py. You can download the model either from the [UER-py Github page](https://github.com/dbiir/UER-py/), or via HuggingFace from the links... | [
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Azaghast/GPT2-SCP-ContainmentProcedures | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
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"GPT2LMHeadModel"
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"no_repeat_ngram_size... | 5 | null | ---
language: Chinese
datasets: CLUECorpusSmall
widget:
- text: "作为电子[MASK]的平台，京东绝对是领先者。如今的刘强[MASK]已经是身价过[MASK]的老板。"
---
# Chinese BART
## Model description
This model is pre-trained by [UER-py](https://arxiv.org/abs/1909.05658).
## How to use
You can use this model directly with a pipeline for text2text genera... | [
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Azaghast/GPT2-SCP-Miscellaneous | [
"pytorch",
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] | text-generation | {
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"no_repeat_ngram_size... | 5 | null | ---
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... | [
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Azizun/Geotrend-10-epochs | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
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"no_repeat... | 6 | null | ---
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... | [
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Azura/data | [] | null | {
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"num_beams... | 0 | 2021-01-26T11:36:00Z | ---
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... | [
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Azuris/DialoGPT-medium-envy | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
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"no_repeat_ngram_size... | 12 | 2021-01-26T11:45:59Z | ---
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... | [
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Azuris/DialoGPT-medium-senorita | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
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"no_repeat_ngram_size... | 14 | 2020-11-25T07:48:39Z | ---
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... | [
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Azuris/DialoGPT-small-envy | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 14 | null | ---
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... | [
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0.0395... |
BAHIJA/distilbert-base-uncased-finetuned-cola | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:glue",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | {
"architectures": [
"DistilBertForSequenceClassification"
],
"model_type": "distilbert",
"task_specific_params": {
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... | 36 | 2021-01-26T11:52:56Z | ---
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... | [
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BE/demo-sentiment2021 | [] | null | {
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"num_beams... | 0 | 2020-12-13T06:06:12Z | ---
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... | [
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0.0395... |
BJTK2/model_name | [] | null | {
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"num_beams... | 0 | null | ---
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... | [
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BOON/electra-xlnet | [] | null | {
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"num_beams... | 0 | null | ---
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... | [
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BSC-LT/roberta-base-bne-capitel-pos | [
"pytorch",
"roberta",
"token-classification",
"es",
"dataset:bne",
"dataset:capitel",
"arxiv:1907.11692",
"arxiv:2107.07253",
"transformers",
"national library of spain",
"spanish",
"bne",
"capitel",
"pos",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"RobertaForTokenClassification"
],
"model_type": "roberta",
"task_specific_params": {
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},
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_... | 14 | null | ---
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... | [
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BSC-LT/roberta-base-bne | [
"pytorch",
"roberta",
"fill-mask",
"es",
"dataset:bne",
"arxiv:1907.11692",
"arxiv:2107.07253",
"transformers",
"national library of spain",
"spanish",
"bne",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
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"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 594 | null | ---
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... | [
-0.03213389217853546,
-0.015320492908358574,
0.006696321535855532,
0.0677206814289093,
0.027387088164687157,
0.005708490498363972,
-0.020708708092570305,
-0.03090532310307026,
-0.01153208315372467,
0.05318799987435341,
0.015115311369299889,
-0.0318807028234005,
0.014258439652621746,
0.0395... |
BSC-LT/roberta-large-bne-capitel-ner | [
"pytorch",
"roberta",
"token-classification",
"es",
"dataset:bne",
"dataset:capitel",
"arxiv:1907.11692",
"arxiv:2107.07253",
"transformers",
"national library of spain",
"spanish",
"bne",
"capitel",
"ner",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"RobertaForTokenClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_... | 5 | null | ---
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... | [
-0.03213389217853546,
-0.015320492908358574,
0.006696321535855532,
0.0677206814289093,
0.027387088164687157,
0.005708490498363972,
-0.020708708092570305,
-0.03090532310307026,
-0.01153208315372467,
0.05318799987435341,
0.015115311369299889,
-0.0318807028234005,
0.014258439652621746,
0.0395... |
BSen/wav2vec2-base-timit-demo-colab | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"transformers",
"generated_from_trainer",
"license:apache-2.0"
] | automatic-speech-recognition | {
"architectures": [
"Wav2Vec2ForCTC"
],
"model_type": "wav2vec2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_s... | 4 | null | ---
language: zh
widget:
- text: "[CLS]国 色 天 香 ， 姹 紫 嫣 红 ， 碧 水 青 云 欣 共 赏 -"
---
# Chinese Couplet GPT2 Model
## Model description
The model is used to generate Chinese couplets. You can download the model either from the [GPT2-Chinese Github page](https://github.com/Morizeyao/GPT2-Chinese), or via HuggingFace fr... | [
-0.02016337960958481,
-0.03720065951347351,
0.0021229214034974575,
0.0594940148293972,
0.026146454736590385,
0.01604272797703743,
-0.017751066014170647,
-0.011928561143577099,
-0.030164455994963646,
0.04572935029864311,
-0.010147051885724068,
-0.002773105166852474,
0.02916732057929039,
0.0... |
BW/TEST | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 14 | null | ---
language: zh
widget:
- text: "[CLS] 万 叠 春 山 积 雨 晴 ，"
- text: "[CLS] 大 漠"
---
# Chinese Poem GPT2 Model
## Model description
The model is used to generate Chinese ancient poems. You can download the model either from the [GPT2-Chinese Github page](https://github.com/Morizeyao/GPT2-Chinese), or via HuggingFac... | [
-0.012686545960605145,
-0.04216211289167404,
-0.003979419358074665,
0.04787653684616089,
0.026614747941493988,
0.013219702988862991,
-0.009252638556063175,
-0.02493971399962902,
-0.024655591696500778,
0.0515415333211422,
0.007759697735309601,
-0.012201434932649136,
0.013400628231465816,
0.... |
Babelscape/wikineural-multilingual-ner | [
"pytorch",
"tensorboard",
"safetensors",
"bert",
"token-classification",
"de",
"en",
"es",
"fr",
"it",
"nl",
"pl",
"pt",
"ru",
"multilingual",
"dataset:Babelscape/wikineural",
"transformers",
"named-entity-recognition",
"sequence-tagger-model",
"license:cc-by-nc-sa-4.0",
"aut... | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 41,608 | null | ---
language: zh
datasets: CLUECorpusSmall
widget:
- text: "内容丰富、版式设计考究、图片华丽、印制精美。[MASK]纸箱内还放了充气袋用于保护。"
---
# Chinese Pegasus
## Model description
This model is pre-trained by [UER-py](https://github.com/dbiir/UER-py/), which is introduced in [this paper](https://arxiv.org/abs/1909.05658).
You can download the s... | [
-0.0409228652715683,
-0.021095918491482735,
0.01348428800702095,
0.05919840931892395,
0.03605920821428299,
0.010785411112010479,
-0.015646565705537796,
-0.04001619666814804,
-0.011698465794324875,
0.0581662580370903,
-0.0030715588945895433,
-0.004603102337568998,
0.0035862880758941174,
0.0... |
Backedman/DialoGPT-small-Anika | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 6 | null | ---
language: zh
widget:
- text: "这本书真的很不错"
---
# Chinese RoBERTa-Base Models for Text Classification
## Model description
This is the set of 5 Chinese RoBERTa-Base classification models fine-tuned by [UER-py](https://arxiv.org/abs/1909.05658). You can download the 5 Chinese RoBERTa-Base classification models eith... | [
-0.03988203778862953,
-0.03371778130531311,
0.007737260777503252,
0.06488902121782303,
0.03670479357242584,
0.03349863737821579,
-0.027255503460764885,
-0.04097726196050644,
-0.031182600185275078,
0.05165496841073036,
0.016989201307296753,
-0.013451557606458664,
0.013590187765657902,
0.033... |
Bagus/SER-LSSED | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
language: zh
widget:
- text: "这本书真的很不错"
---
# Chinese RoBERTa-Base Models for Text Classification
## Model description
This is the set of 5 Chinese RoBERTa-Base classification models fine-tuned by [UER-py](https://arxiv.org/abs/1909.05658). You can download the 5 Chinese RoBERTa-Base classification models eith... | [
-0.03988203778862953,
-0.03371778130531311,
0.007737260777503252,
0.06488902121782303,
0.03670479357242584,
0.03349863737821579,
-0.027255503460764885,
-0.04097726196050644,
-0.031182600185275078,
0.05165496841073036,
0.016989201307296753,
-0.013451557606458664,
0.013590187765657902,
0.033... |
Bagus/wav2vec2-large-xlsr-bahasa-indonesia | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"el",
"dataset:common_voice_id_6.1",
"transformers",
"audio",
"speech",
"bahasa-indonesia",
"license:apache-2.0"
] | automatic-speech-recognition | {
"architectures": [
"Wav2Vec2ForCTC"
],
"model_type": "wav2vec2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_s... | 12 | null | ---
language: zh
widget:
- text: "这本书真的很不错"
---
# Chinese RoBERTa-Base Models for Text Classification
## Model description
This is the set of 5 Chinese RoBERTa-Base classification models fine-tuned by [UER-py](https://arxiv.org/abs/1909.05658). You can download the 5 Chinese RoBERTa-Base classification models eith... | [
-0.03988203778862953,
-0.03371778130531311,
0.007737260777503252,
0.06488902121782303,
0.03670479357242584,
0.03349863737821579,
-0.027255503460764885,
-0.04097726196050644,
-0.031182600185275078,
0.05165496841073036,
0.016989201307296753,
-0.013451557606458664,
0.013590187765657902,
0.033... |
Bagus/wav2vec2-xlsr-japanese-speech-emotion-recognition | [
"pytorch",
"wav2vec2",
"audio-classification",
"ja",
"dataset:jtes",
"transformers",
"audio",
"speech",
"speech-emotion-recognition",
"has_space"
] | audio-classification | {
"architectures": [
"HubertForSequenceClassification"
],
"model_type": "wav2vec2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"... | 26 | null | ---
language: zh
datasets: CLUECorpusSmall
widget:
- text: "最近一趟去北京的[MASK]几点发车"
---
# Chinese word-based RoBERTa Miniatures
## Model description
This is the set of 5 Chinese word-based RoBERTa models pre-trained by [UER-py](https://github.com/dbiir/UER-py/), which is introduced in [this paper](https://arxiv.org/... | [
-0.04114854708313942,
-0.01704065315425396,
-0.0027024440933018923,
0.06920037418603897,
0.03042600490152836,
0.00435927789658308,
-0.014962013810873032,
-0.02840806543827057,
-0.026192953810095787,
0.05360684171319008,
0.02418706752359867,
-0.017559489235281944,
-0.002095214556902647,
0.0... |
Bala/model_name | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
language: zh
datasets: CLUECorpusSmall
widget:
- text: "最近一趟去北京的[MASK]几点发车"
---
# Chinese word-based RoBERTa Miniatures
## Model description
This is the set of 5 Chinese word-based RoBERTa models pre-trained by [UER-py](https://github.com/dbiir/UER-py/), which is introduced in [this paper](https://arxiv.org/... | [
-0.04114854708313942,
-0.01704065315425396,
-0.0027024440933018923,
0.06920037418603897,
0.03042600490152836,
0.00435927789658308,
-0.014962013810873032,
-0.02840806543827057,
-0.026192953810095787,
0.05360684171319008,
0.02418706752359867,
-0.017559489235281944,
-0.002095214556902647,
0.0... |
BalajiSathesh/DialoGPT-small-harrypotter | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 8 | null | ---
language: zh
datasets: CLUECorpusSmall
widget:
- text: "最近一趟去北京的[MASK]几点发车"
---
# Chinese word-based RoBERTa Miniatures
## Model description
This is the set of 5 Chinese word-based RoBERTa models pre-trained by [UER-py](https://github.com/dbiir/UER-py/), which is introduced in [this paper](https://arxiv.org/... | [
-0.04114854708313942,
-0.01704065315425396,
-0.0027024440933018923,
0.06920037418603897,
0.03042600490152836,
0.00435927789658308,
-0.014962013810873032,
-0.02840806543827057,
-0.026192953810095787,
0.05360684171319008,
0.02418706752359867,
-0.017559489235281944,
-0.002095214556902647,
0.0... |
Banshee/dialoGPT-luke-small | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2021-08-23T08:18:52Z | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
license: apache-2.0
---
模型正在测试中 | [
-0.029014524072408676,
-0.004237343557178974,
-0.0033535491675138474,
0.039946284145116806,
0.05031106248497963,
0.02078912779688835,
-0.02017493173480034,
0.03606882691383362,
-0.04416322335600853,
0.07134805619716644,
0.037699729204177856,
0.004460978787392378,
-0.00089086196385324,
0.04... |
BaptisteDoyen/camembert-base-xnli | [
"pytorch",
"tf",
"camembert",
"text-classification",
"fr",
"dataset:xnli",
"transformers",
"zero-shot-classification",
"xnli",
"nli",
"license:mit",
"has_space"
] | zero-shot-classification | {
"architectures": [
"CamembertForSequenceClassification"
],
"model_type": "camembert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 405,474 | 2021-02-26T08:51:05Z | ---
language: zh
datasets: CLUECorpusSmall
widget:
- text: "作为电子extra0的平台，京东绝对是领先者。如今的刘强extra1已经是身价过extra2的老板。"
---
# Chinese T5
## Model description
This is the set of Chinese T5 models pre-trained by [UER-py](https://github.com/dbiir/UER-py/), which is introduced in [this paper](https://arxiv.org/abs/1909.0565... | [
-0.04699774086475372,
-0.022298457100987434,
0.020556241273880005,
0.04813509061932564,
0.02925937809050083,
0.015457632951438427,
-0.035845160484313965,
-0.04138077422976494,
-0.012441020458936691,
0.041747841984033585,
0.028204776346683502,
-0.006008564960211515,
0.0055378214456140995,
0... |
Battlehooks/distilbert-base-uncased-finetuned-squad | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2021-10-20T12:12:01Z | ---
language: hr
datasets:
- mc4
- wikipedia
- multilexnorm
tags:
- lexical normalization
license: apache-2.0
---
# Fine-tuned ByT5-small for MultiLexNorm (Croatian version)
This is the official release of the fine-tuned models for ... | [
-0.017722589895129204,
-0.04086493328213692,
-0.010689516551792622,
0.036929067224264145,
0.023356448858976364,
0.027213245630264282,
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0.04664449766278267,
0.03981814533472061,
-0.01400720328092575,
0.021434340626001358,
0.... |
BatuhanYilmaz/bert-finetuned-mrpc | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2021-10-20T12:12:08Z | ---
language:
- id
- en
- multilingual
datasets:
- mc4
- wikipedia
- multilexnorm
tags:
- lexical normalization
license: apache-2.0
---
# Fine-tuned ByT5-small for MultiLexNorm (Indonesian-English version)
This is the official relea... | [
-0.02169536054134369,
-0.04056122526526451,
-0.011755906045436859,
0.03500138223171234,
0.023343877866864204,
0.02567818947136402,
-0.03757558390498161,
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0.050931867212057114,
0.04440174624323845,
-0.015584086999297142,
0.021538810804486275,
0.0... |
BatuhanYilmaz/bert-finetuned-nerxD | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2021-10-20T12:12:26Z | ---
language: nl
datasets:
- mc4
- wikipedia
- multilexnorm
tags:
- lexical normalization
license: apache-2.0
---
# Fine-tuned ByT5-small for MultiLexNorm (Dutch version)
This is the official release of the fine-tuned models for **t... | [
-0.02427985891699791,
-0.0376712791621685,
-0.009102080017328262,
0.033986568450927734,
0.024830477312207222,
0.024799257516860962,
-0.03618445247411728,
-0.009453141130506992,
-0.033342089504003525,
0.049307890236377716,
0.03897714242339134,
-0.012132757343351841,
0.021283186972141266,
0.... |
BatuhanYilmaz/distilbert-base-uncased-finetuned-squad-d5716d28 | [
"pytorch",
"distilbert",
"fill-mask",
"en",
"dataset:squad",
"arxiv:1910.01108",
"transformers",
"question-answering",
"license:apache-2.0",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"DistilBertForMaskedLM"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repea... | 18 | 2021-10-20T12:12:43Z | ---
language: sr
datasets:
- mc4
- wikipedia
- multilexnorm
tags:
- lexical normalization
license: apache-2.0
---
# Fine-tuned ByT5-small for MultiLexNorm (Serbian version)
This is the official release of the fine-tuned models for *... | [
-0.02039024420082569,
-0.03922629728913307,
-0.013102129101753235,
0.04067271947860718,
0.02582409605383873,
0.02463829703629017,
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0.05153579264879227,
0.04315675050020218,
-0.012057713232934475,
0.019587060436606407,
0.024... |
BatuhanYilmaz/dummy | [] | null | {
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"num_beams... | 0 | 2021-10-20T12:13:01Z | ---
language:
- tr
- de
- multilingual
datasets:
- mc4
- wikipedia
- multilexnorm
tags:
- lexical normalization
license: apache-2.0
---
# Fine-tuned ByT5-small for MultiLexNorm (Turkish-German version)
This is the official release o... | [
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BatuhanYilmaz/marian-finetuned-kde4-en-to-fr | [] | null | {
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"num_beams... | 0 | 2021-05-23T23:27:49Z |
---
language: cs
license: cc-by-nc-sa-4.0
tags:
- RobeCzech
- Czech
- RoBERTa
- ÚFAL
---
# Model Card for RobeCzech
# Model Details
## Model Description
RobeCzech is a monolingual RoBERTa language representation model trained on Czech data.
- **Developed by:** Institute of Formal and Applied Linguistics, Charles U... | [
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BatuhanYilmaz/mlm-finetuned-imdb | [] | null | {
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"num_beams... | 0 | 2021-01-13T22:21:42Z | ---
license: openrail
datasets:
- ncbi_disease
language:
- en
tags:
- disease
- biology
- medical
widget:
- text: "The patient was diagnosed with lung cancer and started chemotherapy."
- text: "The patient has a history of heart disease and high blood pressure."
- text: "The patient was diagnosed with diabetes and pres... | [
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BatuhanYilmaz/mt5-small-finetuned-amazonbooks-en-es | [] | null | {
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"num_beams... | 0 | null | ---
tags:
- conversational
---
# Ginger DialoGPT Model | [
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Baybars/wav2vec2-xls-r-300m-cv8-turkish | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"tr",
"dataset:common_voice",
"transformers",
"common_voice",
"generated_from_trainer",
"hf-asr-leaderboard",
"robust-speech-event",
"license:apache-2.0"
] | automatic-speech-recognition | {
"architectures": [
"Wav2Vec2ForCTC"
],
"model_type": "wav2vec2",
"task_specific_params": {
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"no_repeat_ngram_s... | 5 | 2021-10-30T16:56:35Z | ---
language:
- am
thumbnail: "https://raw.githubusercontent.com/uhh-lt/amharicmodels/master/logo.png?token=AAIB2MYMI6TSIK7CHWYGHKTBQ3FQS"
tags:
- Amharic
- Semetic language
license: "mit"
datasets:
- Amharic corpus from LT group, UHH
widget:
- text: "አበበ <mask> በላ ።"
- text: "የአገሪቱ አጠቃላይ የስንዴ አቅርቦት ሶስት አራተኛው የሚመረተ... | [
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0.03... |
Beelow/model | [] | null | {
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"num_beams... | 0 | null | ---
tags:
- conversational
---
# Peppa Pig DialogGPT-small Model | [
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Beri/legal-qa | [
"pytorch",
"roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"RobertaForQuestionAnswering"
],
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"no_re... | 10 | null | ---
language: pt
license: mit
tags:
- msmarco
- miniLM
- pytorch
- tensorflow
- pt
- pt-br
datasets:
- msmarco
widget:
- text: "Texto de exemplo em português"
inference: false
---
# mMiniLM-L6-v2 Reranker finetuned on mMARCO
## Introduction
mMiniLM-L6-v2-pt-msmarco-v1 is a multilingual miniLM-based model finetuned on a... | [
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0.04... |
BhanuSama/gpt2-finetuned-xsum | [] | null | {
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"num_beams... | 0 | null | ---
language: pt
license: mit
tags:
- msmarco
- t5
- pytorch
- tensorflow
- pt
- pt-br
datasets:
- msmarco
widget:
- text: "Texto de exemplo em português"
inference: false
---
# mt5-base Reranker finetuned on mMARCO
## Introduction
mT5-base-en-pt-msmarco-v2 is a mT5-based model fine-tuned on a bilingual version of MS M... | [
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0.054... |
Bharathdamu/wav2vec2-large-xls-r-300m-hindi-colab | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"dataset:common_voice",
"transformers",
"generated_from_trainer",
"license:apache-2.0"
] | automatic-speech-recognition | {
"architectures": [
"Wav2Vec2ForCTC"
],
"model_type": "wav2vec2",
"task_specific_params": {
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},
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"min_length": null,
"no_repeat_ngram_s... | 4 | null | ---
language: pt
license: mit
tags:
- msmarco
- t5
- pytorch
- tensorflow
- pt
- pt-br
datasets:
- msmarco
widget:
- text: "Texto de exemplo em português"
inference: false
---
# mt5-base Reranker finetuned on mMARCO
## Introduction
mt5-base-mmarco-v1 is a mT5-based model fine-tuned on a multilingual translated version... | [
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0.05... |
Bharathdamu/wav2vec2-model-hindibhasha | [] | null | {
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"num_beams... | 0 | null | ---
language: pt
license: mit
tags:
- msmarco
- t5
- pytorch
- tensorflow
- pt
- pt-br
datasets:
- msmarco
widget:
- text: "Texto de exemplo em português"
inference: false
---
# PTT5-base Reranker finetuned on Portuguese MS MARCO
## Introduction
ptt5-base-msmarco-pt-100k-v1 is a T5-based model pretrained in the BrWac c... | [
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0... |
Bhuvana/t5-base-spellchecker | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"T5ForConditionalGeneration"
],
"model_type": "t5",
"task_specific_params": {
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},
"summarization": {
"early_stopping": true,
"length_penalty": 2,
"max_length": 200,
"min_length": 30,
"no_repeat_ngram_s... | 93 | null | ---
language: pt
license: mit
tags:
- msmarco
- t5
- pytorch
- tensorflow
- pt
- pt-br
datasets:
- msmarco
widget:
- text: "Texto de exemplo em português"
inference: false
---
# PTT5-base Reranker finetuned on Portuguese MS MARCO
## Introduction
ptt5-base-msmarco-pt-10k-v1 is a T5-based model pretrained in the BrWac co... | [
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0... |
BigSalmon/BertaMyWorda | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
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},
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"no_repeat_ngra... | 8 | null | ---
language: pt
license: mit
tags:
- t5
- pytorch
- tensorflow
- pt
- pt-br
datasets:
- brWaC
widget:
- text: "Texto de exemplo em português"
inference: false
---
# Portuguese T5 (aka "PTT5")
## Introduction
PTT5 is a T5 model pretrained in the BrWac corpus, a large collection of web pages in Portuguese, improvi... | [
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... |
BigSalmon/BestMask2 | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
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},
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"min_length": null,
"no_repeat_ngra... | 10 | null | ---
language:
- en
- pt
datasets:
- EMEA
- ParaCrawl 99k
- CAPES
- Scielo
- JRC-Acquis
- Biomedical Domain Corpora
tags:
- translation
metrics:
- bleu
---
# Introduction
This repository brings an implementation of T5 for translation in EN-PT tasks using a modest hardware setup. We propose some changes... | [
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0... |
BigSalmon/DaBlank | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"T5ForConditionalGeneration"
],
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"min_length": 30,
"no_repeat_ngram_s... | 4 | null | ---
language: it
tags:
- sentiment
- Italian
license: mit
widget:
- text: Giuseppe Rossi è un ottimo politico
---
# 🤗 + polibert_SA - POLItic BERT based Sentiment Analysis
## Model description
This model performs sentiment analysis on Italian political twitter sentences. It was trained starting from an instan... | [
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BigSalmon/FormalBerta | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
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"no_repeat_ngra... | 10 | null |
<div align="center">
**⚠️ Disclaimer:**
The huggingface models currently give different results to the detoxify library (see issue [here](https://github.com/unitaryai/detoxify/issues/15)). For the most up to date models we recommend using the models from https://github.com/unitaryai/detoxify
# 🙊 Detoxify... | [
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0.0... |
BigSalmon/GPTT | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
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},
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"no_repeat_ngram_size... | 9 | 2021-12-05T21:04:20Z | ---
language:
- en
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
datasets:
- anli
- multi_nli
- snli
---
# sbert-roberta-large-anli-mnli-snli
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & ... | [
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0.... |
BigSalmon/InformalToFormalLincoln15 | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
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"no_repeat_ngram_size... | 11 | null | ---
language: ja
inference: false
---
# yuyuyui-chatbot
This model is based on [rinna/japanese-gpt2-medium](https://huggingface.co/rinna/japanese-gpt2-medium) and finetuned on Yuyuyui scenario corpus.
## Usage
The model takes a sequence of utterances (context) to generate a subsequent utterance (response). Each utt... | [
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BigSalmon/InformalToFormalLincoln19 | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
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},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 11 | null | ---
language:
- en
tags:
- conversational-search # Example: audio
metrics:
- f1
datasets:
- uva-irlab/canard_quretec
model-index:
- name: QuReTec
results:
- task:
name: Conversational search # Example: Speech Recognition
type: conversational # Example: automatic-speech-recognition
dataset:
... | [
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BigSalmon/InformalToFormalLincoln21 | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"has_space"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
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},
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"no_repeat_ngram_size... | 8 | null | # Nyströmformer
Nyströmformer model for masked language modeling (MLM) pretrained on BookCorpus and English Wikipedia for sequence length 512.
## About Nyströmformer
The Nyströmformer model was proposed in [Nyströmformer: A Nyström-Based Algorithm for Approximating Self-Attention](https://arxiv.org/abs/2102.03902) b... | [
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0.... |
BigSalmon/InformalToFormalLincoln22 | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
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"min_length": null,
"no_repeat_ngram_size... | 6 | null | # YOSO
YOSO model for masked language modeling (MLM) for sequence length 4096.
## About YOSO
The YOSO model was proposed in [You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling](https://arxiv.org/abs/2111.09714) by Zhanpeng Zeng, Yunyang Xiong, Sathya N. Ravi, Shailesh Acharya, Glenn Fun... | [
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0.026... |
BigSalmon/InformalToFormalLincoln23 | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
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},
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"no_repeat_ngram_size... | 5 | 2021-09-17T05:01:44Z | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- null
model-index:
- name: distilgpt2-finetuned-wikitext2
results:
- task:
name: Causal Language Modeling
type: text-generation
---
<!-- This model card has been generated automatically according to the information the Trainer had access... | [
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0... |
BigSalmon/InformalToFormalLincoln25 | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"has_space"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
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},
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"no_repeat_ngram_size... | 10 | null | ---
tags:
- conversational
---
# Rick and Morty DialoGPT Model (small) | [
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BigSalmon/MrLincoln10 | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
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},
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"min_length": null,
"no_repeat_ngram_size... | 5 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-dansk-CV-80
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then ... | [
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BigSalmon/MrLincoln13 | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
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},
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"no_repeat_ngram_size... | 9 | null | [www.github.com/vahmohh/masters-thesis](https://www.github.com/vahmohh/masters-thesis)
The model has been built upon the pre-trained T5 model by fine-tuning it on SQuAD dataset for the porpuse of automatic question and answer generation.
The following format should be used for generating questions.
```sh
generate... | [
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0.016334887593984604,
0.... |
BigSalmon/MrLincoln3 | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 17 | null | ---
language: en
license: mit
datasets:
- AI4Bharat IndicNLP Corpora
---
# IndicBERT
IndicBERT is a multilingual ALBERT model pretrained exclusively on 12 major Indian languages. It is pre-trained on our novel monolingual corpus of around 9 billion tokens and subsequently evaluated on a set of diverse tasks. IndicBER... | [
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0.039... |
BigSalmon/PhraseBerta | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
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},
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"min_length": null,
"no_repeat_ngra... | 10 | 2020-06-13T10:40:02Z | ---
datasets:
- squad
---
# BART-LARGE finetuned on SQuADv1
This is bart-large model finetuned on SQuADv1 dataset for question answering task
## Model details
BART was propsed in the [paper](https://arxiv.org/abs/1910.13461) **BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Transla... | [
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... |
BigSalmon/Rowerta | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngra... | 4 | null | ---
datasets:
- mnli
tags:
- distilbart
- distilbart-mnli
pipeline_tag: zero-shot-classification
---
# DistilBart-MNLI
distilbart-mnli is the distilled version of bart-large-mnli created using the **No Teacher Distillation** technique proposed for BART summarisation by Huggingface, [here](https://github.com/huggingfa... | [
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... |
BigSalmon/SimplifyText | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
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},
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 17 | null | ---
datasets:
- mnli
tags:
- distilbart
- distilbart-mnli
pipeline_tag: zero-shot-classification
---
# DistilBart-MNLI
distilbart-mnli is the distilled version of bart-large-mnli created using the **No Teacher Distillation** technique proposed for BART summarisation by Huggingface, [here](https://github.com/huggingfa... | [
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... |
BigSalmon/T52 | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"T5ForConditionalGeneration"
],
"model_type": "t5",
"task_specific_params": {
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"max_length": null
},
"summarization": {
"early_stopping": true,
"length_penalty": 2,
"max_length": 200,
"min_length": 30,
"no_repeat_ngram_s... | 8 | null | ---
datasets:
- mnli
tags:
- distilbart
- distilbart-mnli
pipeline_tag: zero-shot-classification
---
# DistilBart-MNLI
distilbart-mnli is the distilled version of bart-large-mnli created using the **No Teacher Distillation** technique proposed for BART summarisation by Huggingface, [here](https://github.com/huggingfa... | [
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... |
BigSalmon/T5F | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"T5ForConditionalGeneration"
],
"model_type": "t5",
"task_specific_params": {
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"max_length": null
},
"summarization": {
"early_stopping": true,
"length_penalty": 2,
"max_length": 200,
"min_length": 30,
"no_repeat_ngram_s... | 6 | 2020-09-20T13:54:16Z | ---
datasets:
- mnli
tags:
- distilbart
- distilbart-mnli
pipeline_tag: zero-shot-classification
---
# DistilBart-MNLI
distilbart-mnli is the distilled version of bart-large-mnli created using the **No Teacher Distillation** technique proposed for BART summarisation by Huggingface, [here](https://github.com/huggingfa... | [
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... |
BigSalmon/T5Salmon | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"T5ForConditionalGeneration"
],
"model_type": "t5",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": true,
"length_penalty": 2,
"max_length": 200,
"min_length": 30,
"no_repeat_ngram_s... | 6 | 2020-10-26T18:28:16Z | ---
datasets:
- squad
tags:
- question-generation
- distilt5
- distilt5-qg
widget:
- text: 'generate question: <hl> 42 <hl> is the answer to life, the universe and everything.
</s>'
- text: 'question: What is 42 context: 42 is the answer to life, the universe and
everything. </s>'
license: mit
---
## DistilT5 ... | [
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0.039... |
BigSalmon/TS3 | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible",
"has_space"
] | text2text-generation | {
"architectures": [
"T5ForConditionalGeneration"
],
"model_type": "t5",
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},
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"max_length": null,
"min_length": null,
"no_repeat_n... | 7 | null | ---
datasets:
- squad
tags:
- question-generation
- distilt5
- distilt5-qg
widget:
- text: <hl> 42 <hl> is the answer to life, the universe and everything. </s>
- text: Python is a programming language. It is developed by <hl> Guido Van Rossum
<hl>. </s>
- text: Although <hl> practicality <hl> beats purity </s>
lic... | [
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0.03... |
BigTooth/DialoGPT-Megumin | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
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"min_length": null,
"no_repeat_ngram_size... | 16 | null | # ELECTRA-BASE-DISCRIMINATOR finetuned on SQuADv1
This is electra-base-discriminator model finetuned on SQuADv1 dataset for for question answering task.
## Model details
As mentioned in the original paper: ELECTRA is a new method for self-supervised language representation learning.
It can be used to pre-train transf... | [
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0.... |
Bilz/DialoGPT-small-harrypotter | [] | null | {
"architectures": null,
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},
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"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
datasets:
- squad_v1
license: mit
---
# LONGFORMER-BASE-4096 fine-tuned on SQuAD v1
This is longformer-base-4096 model fine-tuned on SQuAD v1 dataset for question answering task.
[Longformer](https://arxiv.org/abs/2004.05150) model created by Iz Beltagy, Matthew E. Peters, Arman Coha from AllenAI. As the paper... | [
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Bimal/my_bot_model | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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"max_length": 1000
},
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"min_length": null,
"no_repeat_ngram_size... | 10 | null | ---
language:
- multilingual
tags:
- text-2-text-generation
- m2m_100
---
# Model Card for KeywordIdentifier
# Model Details
## Model Description
More information needed
- **Developed by:** Facebook
- **Shared by [Optional]:** Suraj Patil
- **Model type:** Text2Text Generation
- **Language(s) (NLP):** More... | [
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BinksSachary/ShaxxBot | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 9 | null | ---
language: en
datasets:
- librispeech_asr
tags:
- audio
- automatic-speech-recognition
license: apache-2.0
---
TODO: [To be filled]
## Evaluation on LibriSpeech Test
The following script shows how to evaluate this model on the [LibriSpeech](https://huggingface.co/datasets/librispeech_asr) *"clean"* and *"other"*... | [
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Bman/DialoGPT-medium-harrypotter | [] | null | {
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"num_beams... | 0 | null | ---
license: other
tags:
- generated_from_trainer
model-index:
- name: distilbert-allsides
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. -->
# distilbert-allsides
... | [
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BobBraico/distilbert-base-uncased-finetuned-imdb-accelerate | [] | null | {
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"num_beams... | 0 | null | ---
license: other
language: en
datasets:
- valurank/wikirev-bias
---
# DistilROBERTA fine-tuned for bias detection
This model is based on [distilroberta-base](https://huggingface.co/distilroberta-base) pretrained weights, with a classification head fine-tuned to classify text into 2 categories (neutral, biased).
## ... | [
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BrianTin/MTBERT | [
"pytorch",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
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},
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"no_repeat_ngram_size... | 11 | null | ---
tags:
- generated_from_trainer
model-index:
- name: bert-base-uncased-fiqa-flm-sq-flit
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. -->
# bert-base-uncased-fi... | [
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0.01383496355265379,
... |
Brinah/1 | [] | null | {
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},
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"min_length": null,
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"num_beams... | 0 | null | ---
tags:
- generated_from_trainer
model-index:
- name: roberta-base-fiqa-flm-sq-flit
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. -->
# roberta-base-fiqa-flm-sq-... | [
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0.0... |
Brykee/DialoGPT-medium-Morty | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
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},
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 10 | null | ---
language: et
datasets:
- common_voice
- NST Estonian ASR Database
metrics:
- wer
- cer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 Large 53 - Estonian by Vasilis
results:
- task:
name: Speech Recognition
type: ... | [
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Bryson575x/riceboi | [] | null | {
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},
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"num_beams... | 0 | null | ---
language: fi
datasets:
- common_voice
- CSS10 finnish: Single Speaker Speech Dataset
metrics:
- wer
- cer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: V XLSR Wav2Vec2 Large 53 - finnish
results:
- task:
name: Speech Recognition
... | [
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Bubb-les/DisloGPT-medium-HarryPotter | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
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},
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"min_length": null,
"no_repeat_ngram_size... | 8 | null | ---
language: el
datasets:
- common_voice
- CSS10 Greek: Single Speaker Speech Dataset
metrics:
- wer
- cer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: V XLSR Wav2Vec2 Large 53 - greek
results:
- task:
name: Speech Recognition
t... | [
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BumBelDumBel/TRUMP | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers",
"generated_from_trainer",
"license:mit"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
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},
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"min_length": null,
"no_repeat_ngram_size... | 5 | null | ---
language: sv-SE
datasets:
- common_voice
- NST Swedish ASR Database
metrics:
- wer
- cer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: V XLSR Wav2Vec2 Large 53 - Swedish
results:
- task:
name: Speech Recognition
type: automati... | [
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0... |
BumBelDumBel/ZORK-AI-TEST | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers",
"generated_from_trainer",
"license:mit"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
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},
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"min_length": null,
"no_repeat_ngram_size... | 9 | null | ---
language:
- et
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- et
- robust-speech-event
- generated_from_trainer
- hf-asr-leaderboard
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: XLS-R-1B - Estonian
results:
- task:
name: Automatic S... | [
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Buntan/xlm-roberta-base-finetuned-marc-en | [] | null | {
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"num_beams... | 0 | null | Moved here: https://huggingface.co/google/bigbird-base-trivia-itc | [
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Bwehfuk/Ron | [] | null | {
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"num_beams... | 0 | null | Moved here: https://huggingface.co/google/bigbird-pegasus-large-arxiv | [
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CALM/CALM | [] | null | {
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"num_beams... | 0 | null | Moved here: https://huggingface.co/google/bigbird-pegasus-large-bigpatent | [
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0.042235448956489... |
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