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_twostagequadruplet_hier_epochs_1_shard_1 | [
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"no_repeat_ngram_size... | 7 | 2021-06-03T13:08:46Z | ---
tags:
- tabular-classification
- sklearn
dataset:
- wine-quality
widget:
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AnonymousSub/rule_based_roberta_twostagequadruplet_hier_epochs_1_shard_10 | [
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license: mit
tags:
- generated_from_trainer
datasets:
- xtreme
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-panx-de
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: xtreme
type: xtreme
args: PAN-X.de
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AnonymousSub/rule_based_roberta_twostagetriplet_hier_epochs_1_shard_10 | [
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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:
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name: Speech Recognition
type: automatic-speech-recognition
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AnonymousSub/rule_based_roberta_twostagetriplet_hier_epochs_1_shard_1_squad2.0 | [
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"no_re... | 4 | null | ---
language: arz
datasets:
- https://arabicspeech.org/
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 Egyptian Arabic by Othmane Rifki
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AnonymousSub/rule_based_roberta_twostagetriplet_hier_epochs_1_shard_1_wikiqa | [
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"... | 23 | null | ---
language: ary
datasets:
- mgb5
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 Moroccan Arabic dialect by Othmane Rifki
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
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AnonymousSub/rule_based_twostage_quadruplet_epochs_1_shard_1 | [
"pytorch",
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language: ar
datasets:
- https://arabicspeech.org/
tags:
- audio
- automatic-speech-recognition
- speech
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 Egyptian by Zaid Alyafeai and Othmane Rifki
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
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AnonymousSub/unsup-consert-base_copy | [
"pytorch",
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"transformers"
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"no_repeat_ngram_size": nul... | 6 | 2021-08-21T11:25:17Z | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model_index:
- name: finetuned-bert-mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: mrpc
metric:
name: F1
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AnonymousSubmission/pretrained-model-1 | [] | null | {
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"num_beams... | 0 | null | ## ParsTwiNER: Transformer-based Model for Named Entity Recognition at Informal Persian
An open, broad-coverage corpus and model for informal Persian named entity recognition collected from Twitter.
Paper presenting ParsTwiNER: [2021.wnut-1.16](https://aclanthology.org/2021.wnut-1.16/)
---
## Results
The following tab... | [
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AntonClaesson/finetuning_test | [] | null | {
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"num_beams... | 0 | null | {0: 'Anorexia',
1: 'Anxiety',
2: 'Bullying',
3: 'Care',
4: 'Creativity',
5: 'Culture',
6: 'Depression',
7: 'Friends',
8: 'Getting help',
9: 'Happiness',
10: 'Helping others',
11: 'Helping yourself',
12: 'Hope',
13: 'Learning',
14: 'Life Issues',
15: 'Mental Health',
16: 'Mental Health Matters',
17: 'Me... | [
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Aplinxy9plin/toxic-detection-rus | [] | null | {
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language: english
datasets:
- bioASQ
pipeline_tag: question-answering
license: mit
---
# T5-base model fine-tuned on BioASQ for Biological Question Answering 👩⚕️👨⚕️
[Google's T5-base](https://huggingface.co/t5-base) fine-tuned on [BioASQ](https://github.com/dmis-lab/biobert) (secondary task) for **Q&A** downst... | [
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Apoorva/k2t-test | [
"pytorch",
"t5",
"text2text-generation",
"en",
"transformers",
"keytotext",
"k2t",
"Keywords to Sentences",
"autotrain_compatible"
] | text2text-generation | {
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"no_repeat_ngram_s... | 7 | null | ---
language: tr
datasets:
- TQUAD
tags:
- question-answering
- question-generation
- multitask-model
license: apache-2.0
---
# mT5-small based Turkish Multitask (Answer Extraction, Question Generation and Question Answering) System
[Google's Multilingual T5-small](https://github.com/google-research/multilingual-t5... | [
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Appolo/TestModel | [] | null | {
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language: tr
datasets:
- TQUAD
pipeline_tag: question-answering
license: mit
---
# mT5-small based Turkish Question Answering System
[Google's Multilingual T5-small](https://github.com/google-research/multilingual-t5) is fine-tuned on [Turkish Question Answering dataset](https://github.com/TQuad/turkish-nlp-qa-da... | [
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ArBert/albert-base-v2-finetuned-ner-agglo-twitter | [
"pytorch",
"tensorboard",
"albert",
"token-classification",
"transformers",
"autotrain_compatible"
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"no_re... | 27 | null | ---
language: tr
datasets:
- MLSUM
pipeline_tag: summarization
license: mit
---
# mT5-small based Turkish Summarization System
[Google's Multilingual T5-small](https://github.com/google-research/multilingual-t5) is fine-tuned on [MLSUM Turkish news dataset](https://github.com/recitalAI/MLSUM) for **Summarization** do... | [
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ArBert/albert-base-v2-finetuned-ner-agglo | [
"pytorch",
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"albert",
"token-classification",
"transformers",
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] | token-classification | {
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"no_re... | 8 | null | ---
language:
- tr
datasets:
- common_voice
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: Ozcan Gundes XLSR Wav2Vec2 Large Turkish
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
... | [
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ArBert/albert-base-v2-finetuned-ner-kmeans | [
"pytorch",
"tensorboard",
"albert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
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"no_re... | 8 | 2021-08-06T14:26:53Z | ---
tags:
- text2text-generation
library_name: generic
---
random test repo | [
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ArBert/bert-base-uncased-finetuned-ner-agglo | [] | null | {
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"num_beams... | 0 | 2021-05-03T02:46:38Z | ---
datasets:
- squad
tags:
- question-generation
widget:
- text: "Harry Potter is a series of seven fantasy novels written by British author, [HL]J. K. Rowling[HL]."
---
# Transformer QG on SQuAD
HLQG is Proposed by [Ying-Hong Chan & Yao-Chung Fan. (2019). A Re-current BERT-based Model for Question Generation.](https... | [
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ArBert/bert-base-uncased-finetuned-ner-gmm | [] | null | {
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datasets:
- squad
tags:
- question-generation
widget:
- text: "Harry Potter is a series of seven fantasy novels written by British author, [HL]J. K. Rowling[HL]."
---
# Transformer QG on SQuAD
HLQG is Proposed by [Ying-Hong Chan & Yao-Chung Fan. (2019). A Re-current BERT-based Model for Question Generation.](https... | [
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ArBert/bert-base-uncased-finetuned-ner-kmeans-twitter | [] | null | {
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"num_beams... | 0 | null | ## Usage
Please use BertTokenizerFast as tokenizer instead of AutoTokenizer.
請使用 BertTokenizerFast 而非 AutoTokenizer。
```
from transformers import (
BertTokenizerFast,
AutoModelForCausalLM,
)
tokenizer = BertTokenizerFast.from_pretrained('p208p2002/gpt2-drcd-qg-hl')
model = AutoModelForCausalLM.from_pretrained('p2... | [
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ArBert/bert-base-uncased-finetuned-ner | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
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},
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"no_repeat... | 8 | null | ---
datasets:
- squad
tags:
- question-generation
widget:
- text: "Harry Potter is a series of seven fantasy novels written by British author, [HL]J. K. Rowling[HL]."
---
# Transformer QG on SQuAD
HLQG is Proposed by [Ying-Hong Chan & Yao-Chung Fan. (2019). A Re-current BERT-based Model for Question Generation.](https... | [
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ArBert/roberta-base-finetuned-ner-agglo | [] | null | {
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"num_beams... | 0 | null | # EQGG: Educational Question Group Generation
<span>
<a target="_blank" href="https://github.com/p208p2002/Neural-Question-Group-Generation">
<img src="https://img.shields.io/badge/GitHub-100000?style=for-the-badge&logo=github&logoColor=white">
</a>
<a target="_blank" href="https://huggingface.co/p208p2002/qmst-qgg">
... | [
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0.01... |
ArBert/roberta-base-finetuned-ner-gmm-twitter | [] | null | {
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"num_beams... | 0 | null | ---
datasets:
- squad
tags:
- question-generation
widget:
- text: "Harry Potter is a series of seven fantasy novels written by British author, [HL]J. K. Rowling[HL]."
---
# Transformer QG on SQuAD
HLQG is Proposed by [Ying-Hong Chan & Yao-Chung Fan. (2019). A Re-current BERT-based Model for Question Generation.](https... | [
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ArBert/roberta-base-finetuned-ner-gmm | [] | null | {
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"num_beams... | 0 | null | ---
datasets:
- squad
tags:
- question-generation
widget:
- text: "Harry Potter is a series of seven fantasy novels written by British author, [HL]J. K. Rowling[HL]."
---
# Transformer QG on SQuAD
HLQG is Proposed by [Ying-Hong Chan & Yao-Chung Fan. (2019). A Re-current BERT-based Model for Question Generation.](https... | [
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0... |
ArJakusz/DialoGPT-small-stark | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
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"no_repeat_ngram_size... | 8 | null | ---
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
---
# Configuration
`title`: _string_
Display title for the Space
`emoji`: _string_
Space emoji (emoji-only character allowed)
`colorFrom`: _s... | [
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ArashEsk95/bert-base-uncased-finetuned-cola | [] | null | {
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"num_beams... | 0 | 2021-10-27T00:05:14Z | # BERT-STEM
BERT model fine-tuned on Science Technology Engineering and Mathematics (STEM) lessons.
## Install:
To install from pip:
```
pip install bertstem
```
## Quickstart
To encode sentences and get embedding matrix for embedding layers:
```python
from BERT_STEM.BertSTEM import *
bert = BertSTEM()
# Exampl... | [
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ArenaGrenade/char-cnn | [] | null | {
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"num_beams... | 0 | null | ---
language:
- ab
tags:
- automatic-speech-recognition
- common_voice
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: ''
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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Arghyad/Loki_small | [] | null | {
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"num_beams... | 0 | null | ---
language:
- es
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: xls-r-spanish-test
results:
- task:
name: Speech Recognitio... | [
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AriakimTaiyo/DialoGPT-revised-Kumiko | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
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"no_repeat_ngram_size... | 6 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- clinc_oos
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-distilled-clinc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: clinc_oos
type: clinc_oos
args: plus
... | [
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AriakimTaiyo/DialoGPT-small-Kumiko | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
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"no_repeat_ngram_size... | 11 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- clinc_oos
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-clinc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: clinc_oos
type: clinc_oos
args: plus
... | [
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Arkadiusz/Test-model | [] | null | {
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"num_beams... | 0 | 2020-12-10T09:57:14Z | ---
language: id
tags:
- pipeline:summarization
- summarization
- t5
datasets:
- indosum
---
# Indonesian T5 Summarization Small Model
Finetuned T5 small summarization model for Indonesian.
## Finetuning Corpus
`t5-small-indonesian-summarization-cased` model is based on `t5-small-bahasa-summarization-cased` by [hu... | [
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Arnold/wav2vec2-large-xlsr-hausa2-demo-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",
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"no_repeat_ngram_s... | 5 | 2021-11-23T09:28:18Z | ---
language:
- multilingual
- ar
- bg
- de
- el
- en
- es
- fr
- hi
- it
- ja
- nl
- pl
- pt
- ru
- sw
- th
- tr
- ur
- vi
- zh
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlm-roberta-base-language-detection
results: []
---
# xlm-roberta-base-language-detection
This mo... | [
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ArpanZS/search_model | [
"joblib"
] | null | {
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tags:
- conversational
---
# Jake Peralta DialoGPT Model | [
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Aruden/DialoGPT-medium-harrypotterall | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
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],
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"no_repeat_ngram_size... | 6 | null | ---
tags:
- conversational
---
#iron man 1 DialoGPT Model | [
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AryanLala/autonlp-Scientific_Title_Generator-34558227 | [
"pytorch",
"pegasus",
"text2text-generation",
"en",
"dataset:AryanLala/autonlp-data-Scientific_Title_Generator",
"transformers",
"autonlp",
"co2_eq_emissions",
"autotrain_compatible",
"has_space"
] | text2text-generation | {
"architectures": [
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],
"model_type": "pegasus",
"task_specific_params": {
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},
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"n... | 103 | null | ---
tags:
- conversational
---
#Harry Potter DialoGPT MOdel | [
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Ashok/my-new-tokenizer | [] | null | {
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"num_beams... | 0 | null | ---
language: en
license: apache-2.0
datasets:
- glue
---
# Bert-base-cased Fine Tuned Glue Mrpc Demo
This checkpoint was initialized from the pre-trained checkpoint bert-base-cased and subsequently fine-tuned on GLUE task: mrpc using [this](https://colab.research.google.com/drive/162pW3wonGcMMrGxmA-jdxwy1rhqXd90x?usp... | [
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Augustvember/WokkaBot99 | [] | null | {
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"num_beams... | 0 | 2021-11-04T09:55:33Z | ---
language:
- tr
tags:
- automatic-speech-recognition
- common_voice
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: hello_2b_3
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and comp... | [
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"num_beams... | 0 | 2020-09-01T16:15:59Z | # Longformer2Roberta Summarization with 🤗 EncoderDecoder Framework
This model is a Longformer2Roberta model fine-tuned on summarization.
Longformer2Roberta is a `EncoderDecoderModel`, meaning that both the encoder is a `allenai/longformer-base-4096` model and the decoder is a `roberta-base` model. Leveraging the [En... | [
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Ayham/xlnet_gpt2_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
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},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 8 | null | ---
tags:
- automatic-speech-recognition
- timit_asr
- generated_from_trainer
datasets:
- timit_asr
model-index:
- name: unispeech-sat-base-timit-ft
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete... | [
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0... |
Ayham/xlnet_gpt2_summarization_xsum | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:xsum",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
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},
"summarization": {
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"max_length": null,
"min_length": null,
"no_re... | 13 | 2021-10-21T12:12:23Z | ---
tags:
- automatic-speech-recognition
- timit_asr
- generated_from_trainer
datasets:
- timit_asr
model-index:
- name: unispeech-sat-large-timit-ft
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complet... | [
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0... |
AyushPJ/ai-club-inductions-21-nlp-roBERTa-base-squad-v2 | [
"pytorch",
"roberta",
"question-answering",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"RobertaForQuestionAnswering"
],
"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_re... | 8 | null | ---
language: en
datasets:
- librispeech_asr
tags:
- speech
license: apache-2.0
---
# Wav2Vec2-Base
[Facebook's Wav2Vec2](https://ai.facebook.com/blog/wav2vec-20-learning-the-structure-of-speech-from-raw-audio/)
The base model pretrained on 16kHz sampled speech audio. When using the model make sure that your speech... | [
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0.0... |
AyushPJ/test-squad-trained-finetuned-squad | [
"pytorch",
"tensorboard",
"distilbert",
"question-answering",
"dataset:squad",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"DistilBertForQuestionAnswering"
],
"model_type": "distilbert",
"task_specific_params": {
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},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
... | 8 | null | ---
language:
- ab
license: apache-2.0
tags:
- speech-recognition
- common_voice
- generated_from_trainer
model-index:
- name: wav2vec2-common_voice-ab-demo
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and ... | [
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0... |
Azaghast/DistilBART-SCP-ParaSummarization | [
"pytorch",
"bart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"BartForConditionalGeneration"
],
"model_type": "bart",
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},
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"early_stopping": true,
"length_penalty": 2,
"max_length": 142,
"min_length": 56,
"no_repeat_ngr... | 8 | null | ---
language:
- ta
license: apache-2.0
tags:
- automatic-speech-recognition
- common_voice
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-common_voice-tamil
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. Y... | [
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Azaghast/GPT2-SCP-ContainmentProcedures | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
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},
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"min_length": null,
"no_repeat_ngram_size... | 5 | null | ---
language:
- tr
license: apache-2.0
tags:
- speech-recognition
- common_voice
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-common_voice-tr-demo
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
shoul... | [
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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 | 2021-10-08T12:39:10Z | https://wandb.ai/patrickvonplaten/pretraining-wav2vec2/reports/Wav2Vec2-Large--VmlldzoxMTAwODM4?accessToken=wm3qzcnldrwsa31tkvf2pdmilw3f63d4twtffs86ou016xjbyilh55uoi3mo1qzc | [
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0.... |
BOON/electra_qa | [] | null | {
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},
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"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xlsr-turkish-demo-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, then... | [
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0.... |
BSC-LT/roberta-base-biomedical-es | [
"pytorch",
"roberta",
"fill-mask",
"es",
"arxiv:2109.03570",
"arxiv:2109.07765",
"transformers",
"biomedical",
"spanish",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
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},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 161 | null | ---
tags:
- automatic-speech-recognition
- timit_asr
- generated_from_trainer
datasets:
- timit_asr
model-index:
- name: wav2vec2-random
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 re... | [
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0.03... |
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"
],
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},
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"max_length": null,
"min_length": null,
"no_... | 5 | 2021-12-01T16:28:44Z | ---
language:
- tr
tags:
- automatic-speech-recognition
- common_voice
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-xls-r-phoneme-300m-tr
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probabl... | [
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BSC-LT/roberta-large-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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"min_length": null,
"no_... | 13 | 2021-11-05T11:49:01Z | ---
license: apache-2.0
tags:
- automatic-speech-recognition
- multilingual_librispeech
- generated_from_trainer
datasets:
- multilingual_librispeech
model-index:
- name: wav2vec2-xlsr-53-300m-mls-german-ft
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer... | [
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0... |
BW/TEST | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 14 | 2021-05-03T09:03:02Z | ---
language: en
datasets:
- librispeech_asr
tags:
- automatic-speech-recognition
license: apache-2.0
---
## Test model
To test this model run the following code:
```python
from datasets import load_dataset
from transformers import Wav2Vec2ForCTC
import torchaudio
import torch
ds = load_dataset("patrickvonplaten/li... | [
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... |
Babelscape/rebel-large | [
"pytorch",
"safetensors",
"bart",
"text2text-generation",
"en",
"dataset:Babelscape/rebel-dataset",
"transformers",
"seq2seq",
"relation-extraction",
"license:cc-by-nc-sa-4.0",
"model-index",
"autotrain_compatible",
"has_space"
] | text2text-generation | {
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"BartForConditionalGeneration"
],
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},
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"min_length": null,
"no_repe... | 9,458 | 2021-12-17T12:32:14Z | ---
tags:
- automatic-speech-recognition
- librispeech_asr
- generated_from_trainer
- wavlm_libri_finetune
model-index:
- name: wavlm-libri-clean-100h-base-plus
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread ... | [
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0.0... |
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"
],
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},
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"min_length": null,
"no_repeat... | 41,608 | null | ---
tags:
- automatic-speech-recognition
- librispeech_asr
- generated_from_trainer
- wavlm_libri_finetune
model-index:
- name: wavlm-libri-clean-100h-base
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and c... | [
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Badr/model1 | [] | null | {
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"num_beams... | 0 | 2021-12-20T12:01:59Z | ---
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_3_0
- generated_from_trainer
model-index:
- name: xls-r-300m-it-phoneme
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete i... | [
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0.0... |
BatuhanYilmaz/code-search-net-tokenizer1 | [] | null | {
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"num_beams... | 0 | null | ---
language: eu
datasets:
- common_voice
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 Large 53 Basque by pcuenq
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
datas... | [
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-0.02824990637600422,
-0.013986209407448769,
0.... |
BatuhanYilmaz/marian-finetuned-kde4-en-to-fr | [] | null | {
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"num_beams... | 0 | 2020-12-10T14:27:26Z | ---
language: "nl"
thumbnail: "https://github.com/iPieter/RobBERT/raw/master/res/robbert_logo.png"
tags:
- Dutch
- Flemish
- RoBERTa
- RobBERT
license: mit
datasets:
- oscar
- oscar (NL)
- dbrd
- lassy-ud
- europarl-mono
- conll2002
widget:
- text: "Mijn naam is RobBERT en ik ben een taalmodel van de KU Leuven."
---
<... | [
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BatuhanYilmaz/mlm-finetuned-imdb | [] | null | {
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"num_beams... | 0 | 2022-02-01T23:14:03Z | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
model-index:
- name: distilbert-base-uncased-finetuned-emotion
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 r... | [
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Baybars/debateGPT | [] | null | {
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"num_beams... | 0 | 2021-09-05T17:29:30Z | ---
tags:
- conversational
---
# Morty DialoGPT Model | [
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Baybars/wav2vec2-xls-r-1b-turkish | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"tr",
"dataset:common_voice",
"transformers",
"common_voice",
"generated_from_trainer"
] | automatic-speech-recognition | {
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"Wav2Vec2ForCTC"
],
"model_type": "wav2vec2",
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"no_repeat_ngram_s... | 13 | 2020-11-24T05:31:03Z | # Exo-Machina
A deep language model, GPT-2, is trained on scientific manuscripts from NASA's Astrophysical Data System pertaining to extrasolar planets and the references therein. This pilot study uses the abstracts of each article as training data in order to explore correlations in scientific literature from a langu... | [
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Bharathdamu/wav2vec2-large-xls-r-300m-hindi2-colab | [] | null | {
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"num_beams... | 0 | null | ---
language: no
tags:
- translation
widget:
- text: "moscow says deployments in eastern europe increase tensions nato says russia has moved troops to belarus"
- text: "dette er en liten test som er laget av per egil kummervold han er en forsker som tidligere jobbet ved nasjonalbiblioteket"
- text: "tirsdag var ... | [
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Bhumika/roberta-base-finetuned-sst2 | [
"pytorch",
"tensorboard",
"roberta",
"text-classification",
"dataset:glue",
"transformers",
"generated_from_trainer",
"model-index"
] | text-classification | {
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"RobertaForSequenceClassification"
],
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},
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"min_length": null,
"... | 85 | null | ---
license: cc
---
# Multi-Lingual DeUnCaser - Base byT5 Version
The output from Automated Speak Recognition software is usually uncased and without any punctation. This does not make a very readable text.
The DeUnCaser is a sequence-to-sequence model that is reversing this process. It adds punctation, and capi... | [
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Bia18/Beatriz | [] | null | {
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"num_beams... | 0 | null | ---
language: no
license: cc-by-4.0
tags:
- translation
datasets:
- oscar
widget:
- text: Skriv inn en tekst som du ønsker å oversette til en annen målform.
---
# Norwegian mT5 - Translation Bokmål Nynorsk - Development
## Description
This is the development version of the Bokmål-Nynorsk translator. If you want somet... | [
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Biasface/DDDC | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 14 | null | ---
language: no
license: cc-by-4.0
tags:
- translation
datasets:
- oscar
widget:
- text: Skriv inn en tekst som du ønsker å oversette til en annen målform.
---
# Norwegian T5 - Translation Bokmål Nynorsk - Development
## Description
This is the development version of the Bokmål-Nynorsk translator. If you want someth... | [
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0.... |
Biasface/DDDC2 | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
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"early_stopping": null,
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 10 | null | ---
language: no
license: cc-by-4.0
tags:
- translation
datasets:
- oscar
widget:
- text: Skriv inn en tekst som du ønsker å oversette til en annen målform.
---
# 🇳🇴 Bokmål ⇔ Nynorsk 🇳🇴
Norwegian has two relatively similar written languages; Bokmål and Nynorsk. Historically Nynorsk is a written norm based on di... | [
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BigDaddyNe1L/Hhaa | [] | null | {
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"num_beams... | 0 | null | ---
language: no
license: cc-by-4.0
tags:
- norwegian
- GPT2
- casual language modeling
---
# Norwegian GPT-2 - Social
## Description
Experimental Norwegian GPT-2-model trained on a 37GB mainly social corpus.
The following sub-corpora are used:
```bash
wikipedia_download_nb.jsonl
wikipedia_download_nn.jsonl
newspape... | [
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0.... |
BigSalmon/BestMask2 | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
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"no_repeat_ngra... | 10 | 2021-06-28T20:43:03Z | ---
language: no
license: cc-by-4.0
tags:
- norwegian
- GPT2
- casual language modeling
datasets:
- oscar
---
# Norwegian GPT-2 - Oscar
## Description
This is a sample reference model trained only on the Oscar Corpus for a day on a TPU v3-8. Pretrained model on Norwegian language using a causal language modeling (CL... | [
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0.022... |
BigSalmon/DaBlank | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"T5ForConditionalGeneration"
],
"model_type": "t5",
"task_specific_params": {
"conversational": {
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},
"summarization": {
"early_stopping": true,
"length_penalty": 2,
"max_length": 200,
"min_length": 30,
"no_repeat_ngram_s... | 4 | null | # Norwegian GTPNeo Blue.
The first Norwegian GPTNeo model. This one is trained only on a administrative corpus. | [
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0.0... |
BigSalmon/FormalBerta3 | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
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},
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"no_repeat_ngra... | 4 | null | Same as norwegian-roberta-base but with higher learning rate and batch size | [
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BigSalmon/FormalRobertaaa | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
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},
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"min_length": null,
"no_repeat_ngra... | 12 | null | ---
language: no
license: cc-by-4.0
tags:
- seq2seq
datasets:
- Norwegian Nynorsk/Bokmål
---
# 🇳🇴 Norwegian T5 Base model Trained on the NCC🇳🇴
This is a Norwegian T5-base model trained on the Norwegian Colossal Corpus (NCC) on a TPU v3-8. It needs to be finetuned on a specific task before being used for anything... | [
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BigSalmon/GPT2HardArticleEasyArticle | [
"pytorch",
"jax",
"tensorboard",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
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},
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"min_length": null,
"no_repeat_ngram_size... | 7 | null | ---
language: no
license: cc-by-4.0
tags:
- seq2seq
datasets:
- Norwegian Nynorsk/Bokmål
---
# 🇳🇴 Norwegian T5 Base model Trained on the NCC🇳🇴
This is a Norwegian T5-base model trained on the Norwegian Colossal Corpus (NCC) on a TPU v3-8. It needs to be finetuned on a specific task before being used for anything... | [
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BigSalmon/GPTHeHe | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"has_space"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 8 | null | ---
language: no
license: cc-by-4.0
tags:
- summary
datasets:
- oscar
widget:
- text: 'translate Bokmål to Nynorsk: Dette er en test!'
---
# Norwegian T5 - small - Oscar
## Description
This is a sample reference model trained only on the Oscar Corpus for a day on a TPU v3-8. Do not use this model as anything other t... | [
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0.028... |
BigSalmon/GPTNeo350MInformalToFormalLincoln3 | [
"pytorch",
"gpt_neo",
"text-generation",
"transformers",
"has_space"
] | text-generation | {
"architectures": [
"GPTNeoForCausalLM"
],
"model_type": "gpt_neo",
"task_specific_params": {
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},
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"no_repeat_ngram... | 10 | null | ---
language:
- ab
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_7_0
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: ''
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably pro... | [
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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 | null | ---
language:
- fa
- multilingual
thumbnail: https://upload.wikimedia.org/wikipedia/commons/a/a2/Farsi.svg
tags:
- multiple-choice
- mbert
- persian
- farsi
pipeline_tag: text-classification
license: cc-by-nc-sa-4.0
datasets:
- parsinlu
metrics:
- accuracy
---
# Multiple-Choice Question Answering (مدل برای پاسخ به سوا... | [
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0.0517745278775692,
0.0337880402803421,
0.0029108193702995777,
0.003563971258699894,
0.0414... |
BigSalmon/InfillFormalLincoln | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 8 | null | ---
language:
- fa
- multilingual
thumbnail: https://upload.wikimedia.org/wikipedia/commons/a/a2/Farsi.svg
tags:
- multiple-choice
- mt5
- persian
- farsi
license: cc-by-nc-sa-4.0
datasets:
- parsinlu
metrics:
- accuracy
---
# Multiple-Choice Question Answering (مدل برای پاسخ به سوالات چهار جوابی)
This is a mT5-based... | [
0.013195637613534927,
-0.050100140273571014,
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0.054739028215408325,
0.03734278306365013,
0.01604095660150051,
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0.0554167665541172,
0.0315646268427372,
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0.00016241490084212273,
... |
BigSalmon/InformalToFormalLincoln14 | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 5 | null | ---
language:
- fa
- multilingual
thumbnail: https://upload.wikimedia.org/wikipedia/commons/a/a2/Farsi.svg
tags:
- machine-translation
- mt5
- persian
- farsi
license: cc-by-nc-sa-4.0
datasets:
- parsinlu
metrics:
- sacrebleu
---
# Machine Translation (ترجمهی ماشینی)
This is an mT5-based model for machine translatio... | [
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0... |
BigSalmon/InformalToFormalLincoln15 | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 11 | null | ---
language:
- fa
- multilingual
thumbnail: https://upload.wikimedia.org/wikipedia/commons/a/a2/Farsi.svg
tags:
- query-paraphrasing
- mt5
- persian
- farsi
license: cc-by-nc-sa-4.0
datasets:
- parsinlu
- qqp
metrics:
- accuracy
---
# Detection of Paraphrased Queries (تشخصیص سوالات هممعنی)
This is a model for detec... | [
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0.... |
BigSalmon/InformalToFormalLincoln17 | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 12 | 2021-03-06T00:07:13Z | ---
language:
- fa
- multilingual
thumbnail: https://upload.wikimedia.org/wikipedia/commons/a/a2/Farsi.svg
tags:
- entailment
- mt5
- persian
- farsi
license: cc-by-nc-sa-4.0
datasets:
- parsinlu
- snli
metrics:
- accuracy
---
# Textual Entailment (مدل برای پاسخ به استلزام منطقی)
This is a model for textual entailmen... | [
0.009999105706810951,
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0.0626012459397316,
0.017809223383665085,
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0.006956141907721758,
0.03... |
BigSalmon/InformalToFormalLincoln18 | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 8 | 2021-03-10T09:11:15Z |
---
language:
- fa
- multilingual
thumbnail: https://upload.wikimedia.org/wikipedia/commons/a/a2/Farsi.svg
tags:
- reading-comprehension
- mt5
- persian
- farsi
license: cc-by-nc-sa-4.0
datasets:
- parsinlu
- squad
metrics:
- f1
---
# Reading Comprehension (مدل برای پاسخ به درک مطلب)
This is a mT5-based model for read... | [
0.004930265247821808,
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0.05439717322587967,
0.029114630073308945,
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0.007013744208961725,
0.... |
BigSalmon/MrLincoln | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 7 | null | ---
language:
- fa
- multilingual
thumbnail: https://upload.wikimedia.org/wikipedia/commons/a/a2/Farsi.svg
tags:
- multiple-choice
- mt5
- persian
- farsi
license: cc-by-nc-sa-4.0
datasets:
- parsinlu
- commonsenseqa
- arc
- openbookqa
metrics:
- accuracy
---
# Multiple-Choice Question Answering (مدل برای پاسخ به سوال... | [
0.014337640255689621,
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-0.0008778098854236305,
0.05731727182865143,
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0.0535290464758873,
0.028536127880215645,
0.003347090445458889,
-0.0031994390301406384,
... |
BigSalmon/MrLincoln10 | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
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"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 5 | null | ---
language:
- fa
- multilingual
thumbnail: https://upload.wikimedia.org/wikipedia/commons/a/a2/Farsi.svg
tags:
- multiple-choice
- mt5
- persian
- farsi
license: cc-by-nc-sa-4.0
datasets:
- parsinlu
metrics:
- accuracy
---
# Multiple-Choice Question Answering (مدل برای پاسخ به سوالات چهار جوابی)
This is a mT5-based... | [
0.012957680970430374,
-0.04939768835902214,
0.0000718686860636808,
0.054806601256132126,
0.03772951290011406,
0.015329739078879356,
-0.004894530866295099,
0.00005726412928197533,
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0.05596109852194786,
0.031216925010085106,
-0.0007189525058493018,
0.00017931361799128354,... |
BigSalmon/MrLincoln12 | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"has_space"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 9 | null | ---
language:
- fa
- multilingual
thumbnail: https://upload.wikimedia.org/wikipedia/commons/a/a2/Farsi.svg
tags:
- query-paraphrasing
- mt5
- persian
- farsi
license: cc-by-nc-sa-4.0
datasets:
- parsinlu
- qqp
metrics:
- accuracy
---
# Detection of Paraphrased Queries (تشخصیص سوالات هممعنی)
This is a model for detec... | [
0.021851971745491028,
-0.04117327556014061,
-0.010546082630753517,
0.061499375849962234,
0.038772959262132645,
0.025286290794610977,
0.001085371128283441,
0.006524604745209217,
-0.024653544649481773,
0.0565340593457222,
0.01376934815198183,
-0.00008280998736154288,
-0.0025992365553975105,
... |
BigSalmon/MrLincoln125MNeo | [
"pytorch",
"tensorboard",
"gpt_neo",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPTNeoForCausalLM"
],
"model_type": "gpt_neo",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram... | 12 | 2021-03-10T20:46:29Z | ---
language:
- fa
- multilingual
thumbnail: https://upload.wikimedia.org/wikipedia/commons/a/a2/Farsi.svg
tags:
- sentiment
- sentiment-analysis
- mt5
- persian
- farsi
license: cc-by-nc-sa-4.0
datasets:
- parsinlu
metrics:
- accuracy
---
# Sentiment Analysis (آنالیز احساسات)
This is a mT5 model for sentiment analys... | [
0.0038516696076840162,
-0.04820144176483154,
-0.0017890725284814835,
0.06073787435889244,
0.04147394746541977,
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-0.008795727975666523,
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0.06612531840801239,
0.03317373991012573,
-0.009830385446548462,
-0.0008598715648986399,
0... |
BigSalmon/MrLincoln13 | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
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},
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 9 | 2021-03-06T00:06:58Z | ---
language:
- fa
- multilingual
thumbnail: https://upload.wikimedia.org/wikipedia/commons/a/a2/Farsi.svg
tags:
- entailment
- mt5
- persian
- farsi
license: cc-by-nc-sa-4.0
datasets:
- parsinlu
- snli
metrics:
- accuracy
---
# Textual Entailment (مدل برای پاسخ به استلزام منطقی)
This is a model for textual entailmen... | [
0.010335493832826614,
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0.004285930655896664,
0.05457378551363945,
0.03282390534877777,
0.03719722479581833,
-0.014250525273382664,
-0.014867340214550495,
-0.045288607478141785,
0.06291072070598602,
0.01730092242360115,
-0.0036075653042644262,
0.006850783713161945,
0.03... |
BigSalmon/MrLincoln14 | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
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},
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"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2021-03-10T09:10:59Z | ---
language:
- fa
- multilingual
thumbnail: https://upload.wikimedia.org/wikipedia/commons/a/a2/Farsi.svg
tags:
- reading-comprehension
- mt5
- persian
- farsi
license: cc-by-nc-sa-4.0
datasets:
- parsinlu
- squad
metrics:
- f1
---
# Reading Comprehension (مدل برای پاسخ به درک مطلب)
This is a mT5-based model for rea... | [
0.004775139503180981,
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-0.0001207575187436305,
0.04152698069810867,
0.03708615154027939,
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-0.020851198583841324,
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0.0548495352268219,
0.028552092611789703,
-0.012779077515006065,
0.0070282514207065105,
0.0... |
BigSalmon/MrLincoln4 | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 10 | 2021-02-28T00:30:56Z | ---
language:
- fa
- multilingual
thumbnail: https://upload.wikimedia.org/wikipedia/commons/a/a2/Farsi.svg
tags:
- multiple-choice
- parsbert
- persian
- farsi
pipeline_tag: text-classification
license: cc-by-nc-sa-4.0
datasets:
- parsinlu
metrics:
- accuracy
---
# Multiple-Choice Question Answering (مدل برای پاسخ به ... | [
0.02500051259994507,
-0.045966736972332,
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0.0654330626130104,
0.041107356548309326,
0.018395032733678818,
-0.010851018130779266,
-0.004049096722155809,
-0.051525115966796875,
0.05223678797483444,
0.03367643058300018,
0.004710210487246513,
0.0010730251669883728,
0.0410... |
BigSalmon/MrLincoln5 | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 9 | null | ---
language:
- fa
- multilingual
thumbnail: https://upload.wikimedia.org/wikipedia/commons/a/a2/Farsi.svg
tags:
- entailment
- wikibert
- persian
- farsi
license: cc-by-nc-sa-4.0
datasets:
- parsinlu
metrics:
- accuracy
---
# Textual Entailment (مدل برای پاسخ به استلزام منطقی)
This is a model for textual entailment ... | [
0.014043271541595459,
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0.061739806085824966,
0.030056888237595558,
0.03220345079898834,
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0.05848851799964905,
0.030702857300639153,
0.00032425628160126507,
0.00684346491470933,
0... |
BigSalmon/MrLincoln6 | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 9 | null | ---
language:
- fa
- multilingual
thumbnail: https://upload.wikimedia.org/wikipedia/commons/a/a2/Farsi.svg
tags:
- multiple-choice
- wikibert
- persian
- farsi
pipeline_tag: text-classification
license: cc-by-nc-sa-4.0
datasets:
- parsinlu
metrics:
- accuracy
---
# Multiple-Choice Question Answering (مدل برای پاسخ به ... | [
0.02863944135606289,
-0.04897543415427208,
-0.013789623975753784,
0.05426076054573059,
0.03539644181728363,
0.018415534868836403,
-0.011677035130560398,
-0.004260781686753035,
-0.0503675751388073,
0.0562453456223011,
0.033086005598306656,
0.006696684751659632,
0.004662772640585899,
0.04121... |
BigSalmon/Robertsy | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 4 | 2021-08-19T20:10:23Z | ---
language:
- Tagalog
thumbnail:
tags:
- Tagalog
- Mang Bert
license: apache-2.0
datasets:
- OSCAR tl
---
# Mang Bert
## Model description
Fine-Tuned Roberta Model using RobertaForMaskedLM
Tagalog Dataset from OSCAR tl
## Training data
458206 text dataset from OSCAR
| [
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0.04983992502093315,
0.035033173859119415,
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0.011312129907310009,
0.0... |
BinksSachary/ShaxxBot2 | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 12 | null | ---
license: apache-2.0
tags:
- translation
- generated_from_trainer
datasets:
- kde4
metrics:
- bleu
model-index:
- name: marian-finetuned-kde4-en-to-zh_TW
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: kde4
type: kde4
args:... | [
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0.05620281398296356,
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... |
BitanBiswas/mbert-bengali-ner-finetuned-ner | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_repeat... | 4 | null | ---
license: apache-2.0
tags:
- translation
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-amazon-en-es
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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0.010250460356473923,
... |
Blazeolmo/Scrabunzi | [] | null | {
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},
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"num_beams... | 0 | null | ---
license: mit
tags:
- generated_from_keras_callback
model-index:
- name: tf-dummy-model
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. -->
# tf-dummy-model
This model... | [
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0.0151550667360425,
0... |
BlightZz/DialoGPT-medium-Kurisu | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 19 | 2022-02-20T07:00:57Z | ---
license: apache-2.0
tags:
- translation
- generated_from_keras_callback
model-index:
- name: tf-marian-finetuned-kde4-en-to-zh_TW
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... | [
-0.03320399671792984,
-0.02537579834461212,
0.012982534244656563,
0.03205298259854317,
0.03011643886566162,
0.017373688519001007,
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0.04872581362724304,
0.017210638150572777,
-0.01769670844078064,
0.038337986916303635,
0.03... |
BobBraico/bert-finetuned-ner | [] | null | {
"architectures": null,
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- amazon_reviews_multi
metrics:
- accuracy
model-index:
- name: roberta-base-bne-finetuned-amazon_reviews_multi
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: amazon_reviews_multi
type: ... | [
-0.03085523098707199,
0.0029122382402420044,
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0.03367892652750015,
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0... |
BobBraico/distilbert-base-uncased-finetuned-imdb | [] | null | {
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"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-yahd-2
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 re... | [
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0.020813539624214172,
0.046821... |
Boondong/Wandee | [] | null | {
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},
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"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-yahd-twval-hptune
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete ... | [
-0.02136371098458767,
0.010681478306651115,
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0.029040472581982613,
0.0... |
Bosio/full-sentence-distillroberta3-finetuned-wikitext2 | [] | null | {
"architectures": null,
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},
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"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-yahd-twval
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, the... | [
-0.02566550299525261,
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0.060403890907764435,
0.020466621965169907,
-0.045760348439216614,
0.02369948849081993,
0.047... |
BossLee/t5-gec | [
"pytorch",
"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 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-yahd
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 remo... | [
-0.019885040819644928,
0.015546390786767006,
-0.03123829886317253,
0.034145720303058624,
0.04366164654493332,
0.01885792799293995,
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0.05781881511211395,
0.01794499345123768,
-0.04050000011920929,
0.028715945780277252,
0.042... |
Botslity/Bot | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
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},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
tags:
- conversational
---
#Harry Style dialoGPT Model | [
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0.010034341365098953,
... |
Branex/gpt-neo-2.7B | [] | null | {
"architectures": null,
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},
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"num_beams... | 0 | null | ---
language:
- ar
thumbnail: wav2vec2-large-xls-r fine tuned on common voice data for Modern Standard
Arabic
tags:
- automatic-speech-recognition
- hf-asr-leaderboard
- robust-speech-event
license: apache-2.0
datasets:
- mozilla-foundation/common_voice_7_0
metrics:
- WER
model-index:
- name: wav2vec2-large-xls-r-300... | [
-0.0023325136862695217,
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0.02983960695564747,
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0.005853238515555859,
0... |
Brona/model1 | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
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},
"summarization": {
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2021-08-04T19:51:05Z | ---
language:
- en
tags:
- simplification
license: apache-2.0
datasets:
- cnn_dailymail
widget:
- text: "A capsule containing asteroid soil samples landed in the Australian Outback. The precision required to carry out the mission thrilled many.<|endoftext|>"
example_title: "Example 1"
---
# Try out in the Hosted inf... | [
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0.05857193097472191,
0.018151622265577316,
-0.0009216348407790065,
0.016986645758152008,
... |
Brona/poc_de | [] | null | {
"architectures": null,
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"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 | 2022-01-26T17:32:31Z | ---
language:
- en
tags:
- summarization
license: apache-2.0
datasets:
- cnn_dailymail
---
# Try out in the Hosted inference API
In the right panel, you can try to the model (although it only handles a short sequence length).
Enter the document you want to summarize in the panel on the right.
# Model ... | [
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0.05747786909341812,
0.04306894540786743,
0.003889520186930895,
0.015010388568043709,
0.0... |
Brunomezenga/NN | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
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},
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"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2022-01-22T19:53:14Z | ---
language:
- en
tags:
- summarization
license: apache-2.0
datasets:
- cnn_dailymail
metrics:
- rouge
---
# Try out in the Hosted inference API
In the right panel, you can try to the model (although it only handles a short sequence length).
Enter the document you want to summarize in the panel on the right.
# Mode... | [
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0... |
Bryan190/Aguy190 | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
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},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
tags: autonlp
language: en
widget:
- text: "Worry is a down payment on a problem you may never have'. Joyce Meyer. #motivation #leadership #worry"
datasets:
- tweet_eval
model-index:
- name: BERT-tweet-eval-emotion
results:
- task:
name: Sentiment Analysis
type: sentiment-analysis
dataset:
... | [
-0.00025818770518526435,
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0.02910400927066803,
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0.07175042480230331,
0.03387835994362831,
-0.025698034092783928,
0.01208045706152916,
0.... |
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