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 |
|---|---|---|---|---|---|---|---|
Bakkes/BakkesModWiki | [] | null | {
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"num_beams... | 0 | null | # paddle paddle版本的RoFormer
# 需要安装最新的paddlenlp
`pip install git+https://github.com/PaddlePaddle/PaddleNLP.git`
## 预训练模型转换
预训练模型可以从 huggingface/transformers 转换而来，方法如下（适用于roformer模型，其他模型按情况调整）：
1. 从huggingface.co获取roformer模型权重
2. 设置参数运行convert.py代码
3. 例子：
假设我想转换https://huggingface.co/junnyu/roformer_chinese_base 权重... | [
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Bala/model_name | [] | null | {
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"num_beams... | 0 | null | ---
language: en
thumbnail: https://github.com/junnyu
tags:
- pytorch
- electra
- roformer
- rotary position embedding
license: mit
datasets:
- openwebtext
---
# 一、 个人在openwebtext数据集上添加rotary-position-embedding，训练得到的electra-small模型
# 二、 复现结果(dev dataset)
|Model|CoLA|SST|MRPC|STS|QQP|MNLI|QNLI|RTE|Avg.|
|---|---|---|--... | [
-0.034320659935474396,
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Balgow/prod_desc | [] | null | {
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"num_beams... | 0 | null | ---
language: zh
tags:
- bert
- pytorch
widget:
- text: "巴黎是[MASK]国的首都。"
---
https://github.com/dbiir/UER-py/wiki/Modelzoo 中的
MixedCorpus+BertEncoder(large)+MlmTarget
https://share.weiyun.com/5G90sMJ
Pre-trained on mixed large Chinese corpus. The configuration file is bert_large_config.json
## 引用
```tex
@article{... | [
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-0.0017552915960550308,
... |
Banshee/dialoGPT-luke-small | [] | null | {
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"num_beams... | 0 | null | ---
language: zh
tags:
- wobert
inference: False
---
## 介绍
### tf版本
https://github.com/ZhuiyiTechnology/WoBERT
### pytorch版本
https://github.com/JunnYu/WoBERT_pytorch
## 安装(主要为了安装WoBertTokenizer)
```bash
pip install git+https://github.com/JunnYu/WoBERT_pytorch.git
```
## 使用
```python
import torch
from transformers i... | [
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Batsy24/DialoGPT-small-Twilight_EdBot | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
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},
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"min_length": null,
"no_repeat_ngram_size... | 6 | null | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert_finetuning_test
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
type: glue
args: mrpc
metrics:... | [
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0.... |
Battlehooks/distilbert-base-uncased-finetuned-squad | [] | null | {
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"num_beams... | 0 | null | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert_finetuning_test
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
type: glue
args: mrpc
metrics:... | [
-0.014409411698579788,
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0.... |
BatuhanYilmaz/bert-finetuned-mrpc | [] | null | {
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"num_beams... | 0 | null | ---
language: en
tags:
- go-emotion
- text-classification
- pytorch
datasets:
- go_emotions
metrics:
- f1
widget:
- text: "Thanks for giving advice to the people who need it! 👌🙏"
license: mit
---
## Model Description
1. Based on the uncased BERT pretrained model with a linear output layer.
2. Added several commonly-... | [
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0.0... |
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 | {
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"DistilBertForMaskedLM"
],
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"no_repea... | 18 | null | ---
language: en
tags:
- go-emotion
- text-classification
- pytorch
datasets:
- go_emotions
metrics:
- f1
widget:
- text: "Thanks for giving advice to the people who need it! 👌🙏"
license: mit
---
## Model Description
1. Based on the uncased BERT pretrained model with a linear output layer.
2. Added several commonly-... | [
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0... |
BatuhanYilmaz/dummy | [] | null | {
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"num_beams... | 0 | null | ---
tags:
model-index:
- name: bertweet-covid--vaccine-tweets-finetuned
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. -->
# bertweet-covid19-base-uncased-pretrain... | [
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BeIR/query-gen-msmarco-t5-base-v1 | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"T5ForConditionalGeneration"
],
"model_type": "t5",
"task_specific_params": {
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},
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"min_length": 30,
"no_repeat_ngram_s... | 1,816 | null | ---
tags: autonlp
language: unk
widget:
- text: "I love AutoNLP 🤗"
datasets:
- jwuthri/autonlp-data-shipping_status_2
co2_eq_emissions: 32.912881644048
---
# Model Trained Using AutoNLP
- Problem type: Binary Classification
- Model ID: 27366103
- CO2 Emissions (in grams): 32.912881644048
## Validation Metrics
- Lo... | [
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Bee-Garbs/DialoGPT-real-cartman-small | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
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],
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"no_repeat_ngram_size... | 10 | null | Rates Twitter biographies on decision-making preference: Thinking or Feeling. Roughly corresponds to [agreeableness.](https://en.wikipedia.org/wiki/Agreeableness)
Go to your Twitter profile, copy your biography and paste in the inference widget, remove any URLs and press hit!
Trained on self-described personality lab... | [
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Beelow/wav2vec2-ukrainian-model-large | [] | null | {
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"num_beams... | 0 | null | Classifies Twitter biographies as either introverts or extroverts.
Go to your Twitter profile, copy your biography and paste in the inference widget, remove any URLs and press hit!
Trained on self-described personality labels. Interpret as a continuous score, not as a discrete label. Have fun!
Barack Obama: Extrove... | [
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Belin/T5-Terms-and-Conditions | [] | null | {
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"num_beams... | 0 | null | >tr|Q8ZR27|Q8ZR27_SALTY Putative glycerol dehydrogenase OS=Salmonella typhimurium (strain LT2 / SGSC1412 / ATCC 700720) OX=99287 GN=ybdH PE=3 SV=1
MNHTEIRVVTGPANYFSHAGSLERLTDFFTPEQLSHAVWVYGERAIAAARPYLPEAFERA
GAKHLPFTGHCSERHVAQLAHACNDDRQVVIGVGGGALLDTAKALARRLALPFVAIPTIA
ATCAAWTPLSVWYNDAGQALQFEIFDDANFLVLVEPRIILQAPDDYLLAGI... | [
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BenDavis71/GPT-2-Finetuning-AIRaid | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
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"no_repeat_ngram_size... | 10 | null | ---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
datasets:
- kSaluja/autonlp-data-tele_new_5k
co2_eq_emissions: 2.96638567287195
---
# Model Trained Using AutoNLP
- Problem type: Entity Extraction
- Model ID: 557515810
- CO2 Emissions (in grams): 2.96638567287195
## Validation Metrics
- Loss: 0.12... | [
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BenQLange/HF_bot | [] | null | {
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"num_beams... | 0 | 2021-10-18T16:13:48Z | ---
tags:
- conversational
---
#wanda bot go reeeeeeeeeeeeeeeeeeeeee | [
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Bharathdamu/wav2vec2-large-xls-r-300m-hindi | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"dataset:common_voice",
"transformers",
"generated_from_trainer",
"license:apache-2.0"
] | automatic-speech-recognition | {
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"no_repeat_ngram_s... | 10 | null | # Reference extraction in patents
This repository contains a finetuned BERT model that can extract references to scientific literature from patents.
See https://github.com/kaesve/patent-citation-extraction and https://arxiv.org/abs/2101.01039 for more information. | [
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Bharathdamu/wav2vec2-large-xls-r-300m-hindi3-colab | [] | null | {
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"num_beams... | 0 | null | # Reference extraction in patents
This repository contains a finetuned SciBERT model that can extract references to scientific literature from patents.
See https://github.com/kaesve/patent-citation-extraction and https://arxiv.org/abs/2101.01039 for more information.
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Bharathdamu/wav2vec2-model-hindi-stt | [] | null | {
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"num_beams... | 0 | null | ---
tags:
- conversational
---
#Radion DialoGPT Model | [
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0.0387689433991909,
-0.036027319729328156,
0.0026468399446457624,
0.0... |
Bharathdamu/wav2vec2-model-hindibhasha | [] | null | {
"architectures": null,
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},
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"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- squad
model-index:
- name: distilbert-base-uncased-finetuned-squad
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remov... | [
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0.046... |
Bhumika/roberta-base-finetuned-sst2 | [
"pytorch",
"tensorboard",
"roberta",
"text-classification",
"dataset:glue",
"transformers",
"generated_from_trainer",
"model-index"
] | text-classification | {
"architectures": [
"RobertaForSequenceClassification"
],
"model_type": "roberta",
"task_specific_params": {
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"max_length": null
},
"summarization": {
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"max_length": null,
"min_length": null,
"... | 85 | null | ---
language:
- "Python"
thumbnail: "url to a thumbnail used in social sharing"
tags:
- "sentiment analysis"
- "STEM"
- "text classification"
---
Welcome! This is the model built for the sentiment analysis on the STEM course reviews at UCLA.
- Author: Kaixin Wang
- Email: kaixinwang@g.ucla.edu
- Time Update... | [
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Bhuvana/t5-base-spellchecker | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
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],
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"no_repeat_ngram_s... | 93 | null | ---
language: ko
tags:
- KakaoBrain
- KoGPT
- GPT
- GPT3
license: cc-by-nc-4.0
---
# KoGPT
KakaoBrain's Pre-Trained Language Models.
* KoGPT (Korean Generative Pre-trained Transformer)
* [https://github.com/kakaobrain/kogpt](https://github.com/kakaobrain/kogpt)
* [https://huggingface.co/kakaobrain/kogpt](https:... | [
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BigSalmon/DaBlank | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
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"min_length": 30,
"no_repeat_ngram_s... | 4 | null | ## BioELECTRA:Pretrained Biomedical text Encoder using Discriminators
Recent advancements in pretraining strategies in NLP have shown a significant improvement in the performance of models on various text mining tasks. In this paper, we introduce BioELECTRA, a biomedical domain-specific language encoder model that ada... | [
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0.057... |
BigSalmon/Flowberta | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
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},
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"no_repeat_ngra... | 13 | null | ## BioELECTRA:Pretrained Biomedical text Encoder using Discriminators
Recent advancements in pretraining strategies in NLP have shown a significant improvement in the performance of models on various text mining tasks. In this paper, we introduce BioELECTRA, a biomedical domain-specific language encoder model that ada... | [
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0.057... |
BigSalmon/InformalToFormalLincoln16 | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
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"no_repeat_ngram_size... | 8 | null | ---
language: en
tags:
- glossbert
license: mit
datasets:
- SemCor3.0
---
## GlossBERT
A BERT-based model fine-tuned on SemCor 3.0 to perform word-sense-disambiguation by leveraging gloss information. This model is the research output of the paper titled: '[GlossBERT: BERT for Word Sense Disambiguation with Gloss Kno... | [
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BigSalmon/InformalToFormalLincoln18 | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
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"no_repeat_ngram_size... | 8 | null | ---
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: distilbert-base-uncased-CoLA-finetuned-cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: cola
metrics:
- nam... | [
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0... |
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 | null | ---
language:
- hi
license: apache-2.0
tags:
- automatic-speech-recognition
- generated_from_trainer
- hf-asr-leaderboard
- mozilla-foundation/common_voice_7_0
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_7_0
model-index:
- name: ''
results:
- task:
name: Automatic Speech Recognition
... | [
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BigSalmon/Points | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers",
"has_space"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
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"no_repeat_ngram_size... | 13 | null | https://www.geogebra.org/m/cwcveget
https://www.geogebra.org/m/b8dzxk6z
https://www.geogebra.org/m/nqanttum
https://www.geogebra.org/m/pd3g8a4u
https://www.geogebra.org/m/jw8324jz
https://www.geogebra.org/m/wjbpvz5q
https://www.geogebra.org/m/qm3g3ma6
https://www.geogebra.org/m/sdajgph8
https://www.geogebra.org/m/e3ghh... | [
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BigSalmon/T5Salmon | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
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"no_repeat_ngram_s... | 6 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: opus-mt-en-ru-finetuned
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. --... | [
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BigSalmon/T5Salmon2 | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"T5ForConditionalGeneration"
],
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},
"summarization": {
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"length_penalty": 2,
"max_length": 200,
"min_length": 30,
"no_repeat_ngram_s... | 13 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: opus-mt-en-ru-finetuned_v2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment.... | [
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0.... |
BigSalmon/prepositions | [
"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... | 7 | null | ---
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: opus-mt-ru-en-finetuned
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. -->
# opus-mt-ru-en-f... | [
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0.0... |
BigeS/DialoGPT-small-Rick | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
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},
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"no_repeat_ngram_size... | 10 | null | ---
tags: autonlp
language: unk
widget:
- text: "I love AutoNLP 🤗"
datasets:
- kbhugging/autonlp-data-text2sql
co2_eq_emissions: 1.4091714704861447
---
# Model Trained Using AutoNLP
- Problem type: Summarization
- Model ID: 18413376
- CO2 Emissions (in grams): 1.4091714704861447
## Validation Metrics
- Loss: 0.266... | [
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BobBraico/distilbert-base-uncased-finetuned-imdb-accelerate | [] | null | {
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"num_beams... | 0 | 2021-11-09T10:17:25Z | This is an example of how a kenLM model can be downloaded with [PyCTCDecode](https://github.com/kensho-technologies/pyctcdecode) .
Simply run the following code:
```python
from pyctcdecode import LanguageModel
language_model = LanguageModel.load_from_hf_hub("kensho/5gram-spanish-kenLM")
```
The model was trained by... | [
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0.0... |
BobBraico/distilbert-base-uncased-finetuned-imdb | [] | null | {
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"num_beams... | 0 | null | This is an example of how a kenLM model can be downloaded with [PyCTCDecode](https://github.com/kensho-technologies/pyctcdecode) .
Simply run the following code:
```python
from pyctcdecode import BeamSearchDecoderCTC
decoder = BeamSearchDecoderCTC.load_from_hf_hub("kensho/beamsearch_decoder_dummy")
```
The model wa... | [
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BogdanKuloren/continual-learning-paper-embeddings-model | [
"pytorch",
"mpnet",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"MPNetModel"
],
"model_type": "mpnet",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size": n... | 11 | 2021-11-19T15:28:25Z | This is an example of how a kenLM model can be downloaded with [PyCTCDecode](https://github.com/kensho-technologies/pyctcdecode) .
Simply run the following code:
```python
from pyctcdecode import LanguageModel
language_model = LanguageModel.load_from_hf_hub("kensho/dummy_full_language_model")
```
The model was crea... | [
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... |
Bosio/full-sentence-distillroberta3-finetuned-wikitext2 | [] | null | {
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"num_beams... | 0 | null | ---
tags:
- gan
- computer vision
- horse to zebra
license:
- cc0-1.0
---
## Keras Implementation of CycleGAN model using [Horse to Zebra dataset](https://www.tensorflow.org/datasets/catalog/cycle_gan#cycle_ganhorse2zebra) 🐴 -> 🦓
This repo contains the model and the notebook [to this Keras example on CycleGAN](http... | [
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BossLee/t5-gec | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"T5ForConditionalGeneration"
],
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},
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"max_length": 200,
"min_length": 30,
"no_repeat_ngram_s... | 6 | 2022-02-21T05:35:07Z | ---
language:
- en
thumbnail:
tags:
- keras
- tensorflow
- image-classification
library_name: generic
libraries: TensorBoard
license: apache-2.0
metrics:
- accuracy
model-index:
- name: Image-Classification-using-EANet
results:
- task:
type: Image-Classification-using-EANet
dataset:
type: Ima... | [
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Botslity/Bot | [] | null | {
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"num_beams... | 0 | 2021-12-13T18:12:33Z | ---
language:
- en
datasets:
- imdb
tags:
- text-classification
widget:
- text: "I like that movie, but I'm not sure if it's my favorite."
---
## Keras Implementation of Bidirectional LSTMs for Sentiment Analysis on IMDB 🍿🎥
This repo contains the model and the notebook [on Bidirectional LSTMs for Sentiment Anal... | [
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BotterHax/DialoGPT-small-harrypotter | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
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},
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"min_length": null,
"no_repeat_ngram_size... | 8 | null | ---
language:
- en
- fr
tags:
- seq2seq
- translation
license:
- cc0-1.0
---
## Keras Implementation of Character-level recurrent sequence-to-sequence model
This repo contains the model and the notebook [to this Keras example on Character-level recurrent sequence-to-sequence model](https://keras.io/examples/nlp/l... | [
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0.... |
Branex/gpt-neo-2.7B | [] | null | {
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"num_beams... | 0 | 2022-02-07T07:17:24Z | ---
library_name: keras
tags:
- image-to-image
---
# Conditional Generative Adversarial Network
This repo contains the model and the notebook to [this Keras example on Conditional GAN](https://keras.io/examples/generative/conditional_gan/).
Full credits to: [Sayak Paul](https://twitter.com/RisingSayak)
# Background I... | [
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Brendan/cse244b-hw2-roberta | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"RobertaForSequenceClassification"
],
"model_type": "roberta",
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"... | 28 | 2022-02-14T20:18:45Z | ---
tags:
- video-prediction
- moving-mnist
- video-to-video
license: cc0-1.0
---
## Tensorflow Keras Implementation of Next-Frame Video Prediction with Convolutional LSTMs 📽️
This repo contains the models and the notebook [on How to build and train a convolutional LSTM model for next-frame video prediction](https://... | [
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0.009352159686386585,... |
BrianTin/MTBERT | [
"pytorch",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
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},
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"no_repeat_ngram_size... | 11 | null | ---
language: en
tags:
- ConvMixer
- keras-io
license: apache-2.0
datasets:
- cifar10
---
# ConvMixer model
The ConvMixer model is trained on Cifar10 dataset and is based on [the paper](https://arxiv.org/abs/2201.09792v1), [github](https://github.com/locuslab/convmixer).
Disclaimer : This is a demo model for Sayak ... | [
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Brinah/1 | [] | null | {
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"num_beams... | 0 | 2022-02-05T17:44:15Z | ---
tags:
- speech recognition
- ctc
dataset:
- LJSpeech dataset
license: cc0-1.0
---
## Automatic Speech Recognition using CTC model on the 🤗Hub!
Full credits go to [Mohamed Reda Bouadjenek]() and [Ngoc Dung Huynh]().
This repository contains the model from [this notebook on Automatic Speech Recognition using CTC](... | [
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Broadus20/DialoGPT-small-harrypotter | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
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"no_repeat_ngram_size... | 9 | 2021-12-14T11:52:03Z | ---
tags:
- reinforcement learning
- cartpole
- deep deterministic policy gradient
license:
- cc0-1.0
---
## Keras Implementation of Deep Deterministic Policy Gradient ⏱🤖
This repo contains the model and the notebook [to this Keras example on Deep Deterministic Policy Gradient on pendulum](https://keras.io/examples... | [
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Brokette/projetCS | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"transformers"
] | automatic-speech-recognition | {
"architectures": [
"Wav2Vec2ForCTC"
],
"model_type": "wav2vec2",
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"no_repeat_ngram_s... | 4 | 2022-02-10T17:15:47Z | ---
tags:
- computer-vision
- image-segmentation
license:
- cc0-1.0
library_name: keras
---
## Multiclass semantic segmentation using DeepLabV3+
This repo contains the model and the notebook [to this Keras example on Multiclass semantic segmentation using DeepLabV3+](https://keras.io/examples/vision/deeplabv3_plus/).
... | [
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Brona/poc_de | [] | null | {
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"num_beams... | 0 | 2021-12-03T14:36:01Z | ---
tags:
- image-to-text
- generic
library_name: generic
pipeline_tag: image-to-text
widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/cat-1.jpg
example_title: Kedis
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/cat-2.jpg
example_title: Cat in a Crate
- src... | [
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0.0557... |
Brunomezenga/NN | [] | null | {
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"num_beams... | 0 | 2022-02-17T05:50:02Z | ---
license: apache-2.0
library_name: keras
tags:
- image-to-image
---
## Zero-DCE for low-light image enhancement
**Original Author**: [Soumik Rakshit](https://github.com/soumik12345) <br>
**Date created**: 2021/09/18 <br>
**HF Contribution**: [Harveen Singh Chadha](https://github.com/harveenchadha)<br>
**Dataset... | [
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Bryanwong/wangchanberta-ner | [] | null | {
"architectures": null,
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"num_beams... | 0 | 2022-02-18T11:27:07Z | ---
tags:
- computer-vision
- image-classification
license:
- cc0-1.0
library_name: keras
---
## Image Classification using MobileViT
This repo contains the model and the notebook [to this Keras example on MobileViT](https://keras.io/examples/vision/mobilevit/).
Full credits to: [Sayak Paul](https://twitter.com/Risin... | [
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Brykee/BrykeeBot | [] | null | {
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"num_beams... | 0 | null | ---
tags:
- image-segmentation
library_name: keras
---
## Model description
The original idea from Keras examples [Monocular depth estimation](https://keras.io/examples/vision/depth_estimation/) of author [Victor Basu](https://www.linkedin.com/in/victor-basu-520958147/)
Full credits go to [Vu Minh Chien](https://www.l... | [
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Brykee/DialoGPT-medium-Morty | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
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"no_repeat_ngram_size... | 10 | 2022-02-12T04:21:49Z | ---
tags:
- multimodal-entailment
- generic
---
## Tensorflow Keras Implementation of Multimodal entailment.
This repo contains the models [Multimodal Entailment](https://keras.io/examples/nlp/multimodal_entailment/#dataset-visualization).
Credits: [Sayak Paul](https://twitter.com/RisingSayak) - Original Author
HF ... | [
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Bryson575x/riceboi | [] | null | {
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"num_beams... | 0 | null | ---
tags:
- multimodal-entailment
- generic
---
## Tensorflow Keras Implementation of Named Entity Recognition using Transformers.
This repo contains code using the model. [Named Entity Recognition using Transformers](https://keras.io/examples/nlp/ner_transformers/).
Credits: [Varun Singh](https://www.linkedin.com/i... | [
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Bubb-les/DisloGPT-medium-HarryPotter | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
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"no_repeat_ngram_size... | 8 | 2021-12-13T17:44:30Z | ---
tags:
- ocr
- computer vision
- object detection
- image-to-text
license:
- cc0-1.0
---
## Keras Implementation of OCR model for reading captcha 🤖🦹🏻
This repo contains the model and the notebook [to this Keras example on OCR model for reading captcha](https://keras.io/examples/vision/captcha_ocr/).
Full credi... | [
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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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"min_length": null,
"no_repeat_ngram_size... | 5 | null | ---
tags:
- convnet
- mnist
- generative
license:
- cc0-1.0
---
## Keras Implementation of PixelCNN on MNIST 🔢
This repo contains the model [PixelCNN](https://keras.io/examples/generative/pixelcnn/).
Sample images generated:
<img src="https://i.ibb.co/RDWbJBM/image.png" width="120" height='120'> <img src="https://... | [
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BumBelDumBel/ZORK-AI-TEST | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers",
"generated_from_trainer",
"license:mit"
] | text-generation | {
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"no_repeat_ngram_size... | 9 | 2022-02-21T17:10:52Z | ---
tags:
- pointnet
- segmentation
- 3d
- image
license: cc0-1.0
---
## Point cloud segmentation with PointNet
This repo contains [an Implementation of a PointNet-based model for segmenting point clouds.](https://keras.io/examples/vision/pointnet_segmentation/).
Full credits to [Soumik Rakshit](https://github.com/s... | [
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BumBelDumBel/ZORK_AI_FANTASY | [] | null | {
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"num_beams... | 0 | null | ---
tags:
- reinforcement learning
- proximal policy optimization
license:
- cc0-1.0
---
## Keras Implementation of Proximal Policy Optimization on Cartpole Environment 🔨🤖
This repo contains the model and the notebook [to this Keras example on PPO for Cartpole](https://keras.io/examples/rl/ppo_cartpole/).
Full cr... | [
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BumBelDumBel/ZORK_AI_SCIFI | [
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"no_repeat_ngram_size... | 14 | 2022-02-16T13:28:15Z | ---
tags:
- RandAugment
- Image Classification
license: apache-2.0
datasets:
- cifar10
metrics:
- Accuracy
---
## RandAugment for Image Classification for Improved Robustness on the 🤗Hub!
[Paper](https://arxiv.org/abs/1909.13719) | [Keras Tutorial](https://keras.io/examples/vision/randaugment/)
Keras Tutorial Credi... | [
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Buntan/BuntanAI | [] | null | {
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"num_beams... | 0 | 2021-11-04T12:28:15Z | ---
tags:
- image-segmentation
- generic
library_name: generic
dataset:
- oxfort-iit pets
widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/cat-1.jpg
example_title: Kedis
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/cat-2.jpg
example_title: Cat in a Crate
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Buntan/bert-finetuned-ner | [
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"dataset:conll2003",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
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"no_repeat... | 8 | null | ---
library_name: keras
tags:
- image-classification
datasets:
- STL-10
license: apache-2.0
---
# Semi-supervised image classification using contrastive pretraining with SimCLR
## Description
This is a simple image classification model trained with **Semi-supervised image classification using contrastive pretraining ... | [
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Buntan/xlm-roberta-base-finetuned-marc-en | [] | null | {
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"num_beams... | 0 | 2022-01-29T20:52:06Z | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: keras-io/sentiment-analysis
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# keras-... | [
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Bwehfuk/Ron | [] | null | {
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"num_beams... | 0 | null | ---
tags:
- lstm
license:
- cc0-1.0
---
## Keras Implementation of Convolutional Neural Networks for MNIST 1️⃣2️⃣3️⃣
This repo contains the model and the notebook [on Simple MNIST convnet](https://keras.io/examples/vision/mnist_convnet/).
Full credits to: [François Chollet](https://github.com/fchollet)
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CALM/CALM | [] | null | {
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"num_beams... | 0 | 2022-02-03T19:23:42Z | ---
license: mit
tags:
- image-to-image
---
## Notes
* This model is a trained version of the Keras Tutorial [Image Super Resolution](https://keras.io/examples/vision/super_resolution_sub_pixel/)
* The model has been trained on inputs of dimension 100x100 and outputs images of 300x300.
[Link to a pyimagesearch](ht... | [
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CALM/backup | [
"lean_albert",
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library_name: keras
tags:
- image-classification
datasets:
- cifar10
license: apache-2.0
---
A classification model trained with <a href='https://arxiv.org/abs/2004.11362' target='_blank'>**Supervised Contrastive Learning**</a> (Prannay Khosla et al.).
The training procedure was done as seen in the example on <a hr... | [
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CAMeL-Lab/bert-base-arabic-camelbert-ca-ner | [
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"bert",
"token-classification",
"ar",
"arxiv:2103.06678",
"transformers",
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"no_repeat... | 85 | 2022-02-04T11:30:43Z | ---
tags:
- transformers
- swin-transformers
- Keras
- image-classification
dataset:
- CIFAR-100
license: cc0-1.0
---
## Image classification with Swin Transformers on the 🤗Hub!
Author: [Kelvin Idanwekhai](https://twitter.com/KelvinIdan).
[Paper](https://arxiv.org/abs/2103.14030) | [Keras Tutorial](https://keras.io... | [
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CAMeL-Lab/bert-base-arabic-camelbert-ca-pos-egy | [
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"no_repeat... | 16,451 | 2021-12-14T09:02:11Z | ---
tags:
- autoencoder
- time series
- anomaly detection
license:
- cc0-1.0
---
## Keras Implementation of time series anomaly detection using an Autoencoder ⌛
This repo contains the model and the notebook [for this time series anomaly detection implementation of Keras](https://keras.io/examples/timeseries/timeserie... | [
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CAMeL-Lab/bert-base-arabic-camelbert-ca-pos-glf | [
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"tf",
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"no_repeat... | 18 | 2022-02-02T17:37:00Z | ---
tags:
- time-series
- transformers
dataset:
- FordA
license: cc0-1.0
---
## Timeseries classification with a Transformer model on the 🤗Hub!
Full credits go to [Theodoros Ntakouris](https://github.com/ntakouris).
This repository contains the model from [this notebook on time-series classification using the attent... | [
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CAMeL-Lab/bert-base-arabic-camelbert-ca-pos-msa | [
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"no_repeat... | 71 | 2022-01-12T08:59:41Z | ---
datasets:
- squad
license: apache-2.0
tags:
- generated_from_keras_callback
metrics:
- f1
model-index:
- name: transformers-qa
results:
- task:
name: "Question Answering"
type: question-answering
dataset:
type: squad
name: SQuAD
args: en
metrics:
[]
widget:
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CAMeL-Lab/bert-base-arabic-camelbert-ca | [
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"no_repeat_ngram_size... | 580 | 2022-02-17T08:00:12Z | ---
title: Video Vision Transformer on medmnist
emoji: 🧑⚕️
colorFrom: red
colorTo: green
sdk: gradio
app_file: app.py
pinned: false
license: apache-2.0
library_name: keras
---
## Keras Implementation of Video Vision Transformer on medmnist
This repo contains the model [to this Keras example on Video Vision Transfor... | [
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CAMeL-Lab/bert-base-arabic-camelbert-da-ner | [
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"no_repeat... | 42 | null | ---
tags:
- image-classification
- keras
license: apache-2.0
---
# Train a Vision Transformer on small datasets
Author: [Aritra Roy Gosthipaty](https://twitter.com/ariG23498)
[Keras Blog](https://keras.io/examples/vision/vit_small_ds/) | [Colab Notebook](https://colab.research.google.com/github/keras-team/keras-io/bl... | [
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CAMeL-Lab/bert-base-arabic-camelbert-da-poetry | [
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"arxiv:2103.06678",
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] | text-classification | {
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"no_rep... | 37 | 2022-02-04T07:21:24Z | ---
tags:
- image-classification
- keras
license: apache-2.0
---
# Train a Vision Transformer on small datasets
Author: [Jónathan Heras](https://twitter.com/_Jonathan_Heras)
[Keras Blog](https://keras.io/examples/vision/vit_small_ds/) | [Colab Notebook](https://colab.research.google.com/github/keras-team/keras-io/blo... | [
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CAMeL-Lab/bert-base-arabic-camelbert-da-pos-glf | [
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"transformers",
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"autotrain_compatible"
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"no_repeat... | 54 | 2021-07-11T16:33:46Z | ---
language: si
tags:
- sinhala
- gpt2
pipeline_tag: text-generation
widget:
- text: "මම"
---
This is a finetunes version of keshan/sinhala-gpt2 with newswire articles. This was finetuned on ~12MB of data
- Num examples=8395
- Batch size =8
It got a Perplexity of 3.15 | [
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CAMeL-Lab/bert-base-arabic-camelbert-da-pos-msa | [
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"no_repeat... | 27 | null | ---
language: si
tags:
- Sinhala
- text-generation
- gpt2
datasets:
- mc4
---
### Overview
This is a smaller GPT2 model trained on [MC4](https://github.com/allenai/allennlp/discussions/5056) Sinhala dataset. As Sinhala is one of those low resource languages, there are only a handful of models been trained. So, this wo... | [
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CAMeL-Lab/bert-base-arabic-camelbert-da-sentiment | [
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"license:apache-2.0",
"has_space"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
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"no_rep... | 19,850 | 2021-07-12T19:45:07Z | ---
language: si
license: cc-by-4.0
tags:
- sinhala
- roberta
pipeline_tag: fill-mask
widget:
- text: මම සිංහල භාෂාව <mask>
---
# Sinhala roberta on mc4 dataset
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CAMeL-Lab/bert-base-arabic-camelbert-mix-pos-glf | [
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"tf",
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"token-classification",
"ar",
"arxiv:2103.06678",
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"no_repeat... | 132 | 2020-10-13T16:18:37Z | # kevinrobinson/perturbations_table_quickstart model card
This is just for UI smoke testing, and shouldn't be used for anything else.
It's built from https://github.com/PAIR-code/lit/blob/main/lit_nlp/examples/quickstart_sst_demo.py.
| [
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CAMeL-Lab/bert-base-arabic-camelbert-msa-did-madar-twitter5 | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0"
] | text-classification | {
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"no_rep... | 75 | 2021-11-17T04:17:43Z | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- matthews_correlation
model-index:
- name: chinese-bert-wwm-ext-finetuned-cola
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, ... | [
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CLAck/en-vi | [
"pytorch",
"marian",
"text2text-generation",
"en",
"vi",
"dataset:ALT",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | {
"architectures": [
"MarianMTModel"
],
"model_type": "marian",
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},
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"no_repeat_ngram_size... | 8 | 2021-07-17T00:09:14Z | ---
language: bn
tags:
- text generation
- bengali
- gpt2
- bangla
- causal-lm
widget:
- text: "জীবনের মানে "
pipeline_tag: text-generation
---
<!--
---
tags:
- generated_from_trainer
datasets:
- null
model_index:
- name: bengali-lyricist-gpt2
results:
- task:
name: Causal Language Modeling
type: text... | [
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CLAck/vi-en | [
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"text2text-generation",
"en",
"vi",
"dataset:ALT",
"transformers",
"translation",
"license:apache-2.0",
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},
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"no_repeat_ngram_size... | 6 | null | ---
language: en
thumbnail: Keywords to Sentences
tags:
- keytotext
- k2t
- Keywords to Sentences
license: mit
datasets:
- WebNLG
- Dart
metrics:
- NLG
---
# keytotext
Idea is to build a model which w... | [
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CLTL/gm-ner-xlmrbase | [
"pytorch",
"tf",
"xlm-roberta",
"token-classification",
"nl",
"transformers",
"dighum",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
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"XLMRobertaForTokenClassification"
],
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"min_length": null,
... | 2 | null | ---
language: id
tags:
- indogpt
- indobenchmark
- indonlg
license: mit
inference: false
datasets:
- Indo4B+
---
# IndoBART-v2 Model fine-tuned version
Fine-tuned version of IndoBART-v2 with machine translation id->su using default hyperparameter from indoBART paper.
by Ryan Abdurohman
# IndoBART-v2 Model
[IndoBAR... | [
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CLTL/icf-levels-adm | [
"pytorch",
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"nl",
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"... | 33 | null | # Unreliable News Classifier (English)
Trained, validate, and tested using a subset of the NELA-GT-2018 dataset. The dataset is split such that there was no overlap in of news sources between the three sets.
This model used the pre-trained weights of `bert-base-cased` as starting point and was able to achieve 84% accur... | [
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0.0... |
CLTL/icf-levels-att | [
"pytorch",
"roberta",
"text-classification",
"nl",
"transformers",
"license:mit"
] | text-classification | {
"architectures": [
"RobertaForSequenceClassification"
],
"model_type": "roberta",
"task_specific_params": {
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},
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"... | 32 | 2022-01-14T00:02:21Z | # Unreliable News Classifier (English)
Trained, validate, and tested using a subset of the NELA-GT-2018 dataset. The dataset is split such that there was no overlap in of news sources between the three sets.
This model used the pre-trained weights of `distilbert-base-cased` as starting point (only 4 layers) and was abl... | [
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0.0193... |
CSResearcher/TestModel | [
"license:mit"
] | null | {
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"num_beams... | 0 | 2022-01-26T19:43:59Z | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-kika4_my-colab
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, th... | [
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0.02... |
Cameron/BERT-rtgender-opgender-annotations | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
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},
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"min_length": null,
"no_rep... | 33 | null | ---
language:
- id
license: apache-2.0
tags:
- automatic-speech-recognition
- hf-asr-leaderboard
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_7_0
metrics:
- wer
- cer
model-index:
- name: wav2vec2-large-xls-r-300m-Indonesian
results:
- task:
type: automatic-speech-recognition
name: ... | [
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Camzure/MaamiBot-test | [
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"text-generation",
"transformers",
"conversational"
] | conversational | {
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],
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"no_repeat_ngram_size... | 9 | null | ---
language:
- sv-SE
license: apache-2.0
tags:
- automatic-speech-recognition
- robust-speech-event
- hf-asr-leaderboard
datasets:
- mozilla-foundation/common_voice_8_0
metrics:
- wer
- cer
model-index:
- name: wav2vec2-xls-r-300m-swedish
results:
- task:
type: automatic-speech-recognition
name: Speech... | [
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dccuchile/albert-large-spanish-finetuned-pawsx | [
"pytorch",
"albert",
"text-classification",
"transformers"
] | text-classification | {
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"AlbertForSequenceClassification"
],
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},
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"no... | 25 | null | ---
language: en
tags:
- exbert
license: mit
datasets:
- bookcorpus
- wikipedia
---
# RoBERTa base model
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1907.11692) and first released in
[this repository](https://github.com... | [
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dccuchile/albert-tiny-spanish-finetuned-mldoc | [
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"no... | 32 | null | ---
language:
- en
tags:
- pytorch
- token-classification
- nominalizations
datasets:
- kleinay/qanom
---
# Nominalization Detector
This model identifies "predicative nominalizations", that is, nominalizations that carry an eventive (or "verbal") meaning in context. It is a `bert-base-cased` pretrained model, fine-tu... | [
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dccuchile/albert-xxlarge-spanish-finetuned-xnli | [
"pytorch",
"albert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"AlbertForSequenceClassification"
],
"model_type": "albert",
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"min_length": null,
"no... | 68 | null | ---
language: ar
datasets:
- common_voice
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 Arabic by Othmane Rifki
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset... | [
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dccuchile/albert-large-spanish | [
"pytorch",
"tf",
"albert",
"pretraining",
"es",
"dataset:large_spanish_corpus",
"transformers",
"spanish",
"OpenCENIA"
] | null | {
"architectures": [
"AlbertForPreTraining"
],
"model_type": "albert",
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},
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"min_length": null,
"no_repeat_ngr... | 75 | null | ---
tags:
- conversational
---
#Harry Potter model | [
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dccuchile/bert-base-spanish-wwm-cased-finetuned-ner | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
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"no_repeat... | 81 | 2021-09-15T14:19:15Z | ---
language: en
tags:
- bart
- seq2seq
- summarization
license: apache-2.0
datasets:
- samsum
widget:
- text: "Hannah: Hey, do you have Betty's number?\nAmanda: Lemme check\nAmanda: Sorry,\
\ can't find it.\nAmanda: Ask Larry\nAmanda: He called her last time we were at\
\ the park together\nHannah: I don't kno... | [
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CheonggyeMountain-Sherpa/kogpt-trinity-poem | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
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],
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"no_repeat_ngram_size... | 15 | null | ---
tags:
- spacy
- token-classification
language:
- en
license: mit
model-index:
- name: en_core_med7_lg
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.8649613325
- name: NER Recall
type: recall
value: 0.... | [
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CheonggyeMountain-Sherpa/kogpt-trinity-punct-wrapper | [
"ko",
"gpt2",
"license:cc-by-nc-sa-4.0"
] | null | {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
tags:
- spacy
- token-classification
language:
- en
license: mit
model-index:
- name: en_core_med7_trf
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.8822157434
- name: NER Recall
type: recall
value: 0... | [
-0.011285301297903061,
-0.0020749918185174465,
-0.002944985870271921,
0.031314603984355927,
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0.04344315826892853,
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0.008764410391449928,
0... |
Chertilasus/main | [] | null | {
"architectures": null,
"model_type": null,
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},
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"min_length": null,
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"num_beams... | 0 | null | Converted for Tensorflow
```
!pip install transformers sentencepiece
from transformers import TFAutoModel, AutoTokenizer
name = "ai4bharat/indic-bert"
model = TFAutoModel.from_pretrained(name, from_pt=True)
tokenizer = AutoTokenizer.from_pretrained(name)
model.save_pretrained("local-indic-bert")
tokenizer.save_pretrai... | [
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0... |
Chinmay/mlindia | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
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},
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"min_length": null,
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"num_beams... | 0 | null | Converted for Tensorflow
```
!pip install transformers sentencepiece
from transformers import TFAutoModel, AutoTokenizer
name = "xlm-roberta-base"
model = TFAutoModel.from_pretrained(name, from_pt=True)
tokenizer = AutoTokenizer.from_pretrained(name)
model.save_pretrained("local-xlm-roberta-base")
tokenizer.save_pretra... | [
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0.008298590779304504,
... |
Chiuchiyin/DialoGPT-small-Donald | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 7 | null | Converted for Tensorflow
```
name = "xlm-roberta-large"
!rm -rf local
!git clone https://huggingface.co/kornesh/"$name" local
model = TFAutoModel.from_pretrained(name, from_pt=True)
tokenizer = AutoTokenizer.from_pretrained(name)
model.save_pretrained("local")
tokenizer.save_pretrained("local")
!cd local/ && git lfs in... | [
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Chiuchiyin/Donald | [] | null | {
"architectures": null,
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},
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"num_beams... | 0 | 2021-04-15T00:54:47Z | ---
language: "en"
tags:
- twitter
- stance-detection
- election2020
- politics
license: "gpl-3.0"
---
# Pre-trained BERT on Twitter US Election 2020 for Stance Detection towards Joe Biden (KE-MLM)
Pre-trained weights for **KE-MLM model** in [Knowledge Enhance Masked Language Model for Stance Detection](https://www.a... | [
-0.006326775997877121,
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0.020739801228046417,
0... |
ChoboAvenger/DialoGPT-small-DocBot | [] | null | {
"architectures": null,
"model_type": null,
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},
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"max_length": null,
"min_length": null,
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"num_beams... | 0 | null | ---
language: "en"
tags:
- twitter
- stance-detection
- election2020
- politics
license: "gpl-3.0"
---
# Pre-trained BERT on Twitter US Election 2020 for Stance Detection towards Joe Biden (f-BERT)
Pre-trained weights for **f-BERT** in [Knowledge Enhance Masked Language Model for Stance Detection](https://www.aclweb.... | [
-0.0029679113067686558,
-0.016059935092926025,
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0.05696893483400345,
0.01851351000368595,
-0.02840529754757881,
0.019464632496237755,
0.0... |
ChoboAvenger/DialoGPT-small-joshua | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
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},
"summarization": {
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"max_length": null,
"min_length": null,
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"num_beams... | 0 | null | ---
language: "en"
tags:
- twitter
- stance-detection
- election2020
- politics
license: "gpl-3.0"
---
# Pre-trained BERT on Twitter US Election 2020 for Stance Detection towards Donald Trump (KE-MLM)
Pre-trained weights for **KE-MLM model** in [Knowledge Enhance Masked Language Model for Stance Detection](https://ww... | [
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0.05208626389503479,
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-0.01607666164636612,
0.01509603951126337,
0.023... |
ChrisP/xlm-roberta-base-finetuned-marc-en | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
language: "en"
tags:
- twitter
- stance-detection
- election2020
- politics
license: "gpl-3.0"
---
# Pre-trained BERT on Twitter US Election 2020 for Stance Detection towards Donald Trump (f-BERT)
Pre-trained weights for **f-BERT** in [Knowledge Enhance Masked Language Model for Stance Detection](https://www.aclw... | [
-0.01077963039278984,
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0.... |
ChrisVCB/DialoGPT-medium-cmjs | [
"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... | 7 | null | ---
language: "en"
tags:
- twitter
- masked-token-prediction
- election2020
- politics
license: "gpl-3.0"
---
# Pre-trained BERT on Twitter US Political Election 2020
Pre-trained weights for [Knowledge Enhance Masked Language Model for Stance Detection](https://www.aclweb.org/anthology/2021.naacl-main.376), NAACL 202... | [
-0.016115235164761543,
-0.01427055150270462,
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0.060996413230895996,
0.007857867516577244,
-0.024552518501877785,
0.0265443567186594,
0.... |
Chun/w-en2zh-hsk | [
"pytorch",
"marian",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MarianMTModel"
],
"model_type": "marian",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 1 | 2021-08-27T05:59:33Z | ---
tags:
- Conversational
---
# Tony Stark DialoGPT Model | [
-0.050190314650535583,
0.020672420039772987,
0.008030409924685955,
0.02788759022951126,
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0.0004272998485248536,
0.05997179448604584,
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0.024159936234354973,
0.03... |
Chun/w-en2zh-otm | [
"pytorch",
"mbart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MBartForConditionalGeneration"
],
"model_type": "mbart",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_re... | 7 | 2022-02-19T07:59:10Z | # SaShiMi
> **It's Raw! Audio Generation with State-Space Models**\
> Karan Goel, Albert Gu, Chris Donahue, Christopher Ré\
> Paper: https://arxiv.org/pdf/2202.09729.pdf
This repository contains a release of the artifacts for the SaShiMi paper. To use our code and... | [
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0.02... |
Chun/w-zh2en-mtm | [
"pytorch",
"mbart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MBartForConditionalGeneration"
],
"model_type": "mbart",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_re... | 8 | 2022-01-20T10:41:07Z | ---
language: ko
datasets:
- kresnik/zeroth_korean
tags:
- speech
- audio
- automatic-speech-recognition
license: apache-2.0
model-index:
- name: 'Wav2Vec2 XLSR Korean'
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Zeroth Kore... | [
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-0.03786557540297508,
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0.0134... |
Chungu424/qazwsx | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
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},
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"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2020-05-21T16:09:24Z | ---
language: ko
---
# 📈 Financial Korean ELECTRA model
Pretrained ELECTRA Language Model for Korean (`finance-koelectra-base-discriminator`)
> ELECTRA is a new method for self-supervised language representation learning. It can be used to
> pre-train transformer networks using relatively little compute. ELECTRA mo... | [
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0.014399535953998566,
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... |
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