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 |
|---|---|---|---|---|---|---|
CAMeL-Lab/bert-base-arabic-camelbert-ca | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
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},
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"min_length": null,
"no_repeat_ngram_size... | 580 | null | ---
language: "en"
tags:
- English
- Bible
dataset:
- English Bible Translation Dataset
- Link: https://www.kaggle.com/oswinrh/bible
inference: false
---
## Dataset
English Bible Translation Dataset (https://www.kaggle.com/oswinrh/bible)
*NOTE:* It is `roberta-base` fine-tuned (for MLM objective) for 1 epoch (u... |
CAMeL-Lab/bert-base-arabic-camelbert-da-poetry | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:1905.05700",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 37 | null | ---
language:
- English
tags:
- EManuals
- customer support
- QA
- bert
---
Refer to https://aclanthology.org/2021.findings-emnlp.392/ for the paper and https://sites.google.com/view/emanualqa/home for the project website
## Citation
Please cite the work if you would like to use it.
```
@inproceedings{nandy-eta... |
CAMeL-Lab/bert-base-arabic-camelbert-da-pos-glf | [
"pytorch",
"tf",
"bert",
"token-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 54 | null | ---
language:
- English
tags:
- Europarl
- roberta
datasets:
- Europarl
---
Refer to https://aclanthology.org/2021.semeval-1.87/
## Citation
If you use this model in your work, please add the following citation -
```
@inproceedings{nandy-etal-2021-cs60075,
title = "cs60075{\_}team2 at {S}em{E}val-2021 Task... |
CAMeL-Lab/bert-base-arabic-camelbert-da-sentiment | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"has_space"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 19,850 | null | ---
language: en
tags:
- spanbert
datasets:
- ade_corpus_v2
widget:
- text: "Having fever after taking paracetamol."
example_title: "NER"
- text: "Birth defects associated with thalidomide."
example_title: "NER"
- text: "Deafness and kidney failure associated with gentamicin (an antibiotic)."
example_title: "NER"... |
CAMeL-Lab/bert-base-arabic-camelbert-mix-did-madar-corpus26 | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
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},
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"min_length": null,
"no_rep... | 45 | null | # Dataset
---
---
datasets:
- covid_qa_deepset
---
---
Covid 19 question answering data obtained from [covid_qa_deepset](https://huggingface.co/datasets/covid_qa_deepset).
# Original Repository
Repository for the fine tuning, inference and evaluation scripts can be found [here](https://github.com/abhijithneilabrah... |
CAMeL-Lab/bert-base-arabic-camelbert-mix-did-nadi | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"max_length": null,
"min_length": null,
"no_rep... | 63 | null | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# {MODEL_NAME}
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like cluster... |
CAMeL-Lab/bert-base-arabic-camelbert-mix-pos-glf | [
"pytorch",
"tf",
"bert",
"token-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 132 | null | ---
language:
- en
license: apache-2.0
datasets:
- squad_v2
model-index:
- name: abhilash1910/albert-squad-v2
results:
- task:
type: question-answering
name: Question Answering
dataset:
name: squad_v2
type: squad_v2
config: squad_v2
split: validation
metrics:
- type: ... |
CAMeL-Lab/bert-base-arabic-camelbert-mix-sentiment | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 855 | null | ---
tags:
- finance
---
# Roberta Masked Language Model Trained On Financial Phrasebank Corpus
This is a Masked Language Model trained with [Roberta](https://huggingface.co/transformers/model_doc/roberta.html) on a Financial Phrasebank Corpus.
The model is built using Huggingface transformers.
The model can be found... |
CAMeL-Lab/bert-base-arabic-camelbert-msa-quarter | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 12 | null | ---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
datasets:
- abhishek/autonlp-data-ferd1
---
# Model Trained Using AutoNLP
- Problem type: Binary Classification
- Model ID: 2652021
## Validation Metrics
- Loss: 0.3934604227542877
- Accuracy: 0.8411030860144452
- Precision: 0.8201550387596899
- Rec... |
CLTL/icf-levels-att | [
"pytorch",
"roberta",
"text-classification",
"nl",
"transformers",
"license:mit"
] | text-classification | {
"architectures": [
"RobertaForSequenceClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
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"min_length": null,
"... | 32 | null | Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on German using the Common Voice dataset. When using this model, make sure that your speech input is sampled at 16kHz.
As capitalization is an important part of the German language (eg. Sie vs. sie).
I trained a model using ... |
CLTL/icf-levels-fac | [
"pytorch",
"roberta",
"text-classification",
"nl",
"transformers",
"license:mit"
] | text-classification | {
"architectures": [
"RobertaForSequenceClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"... | 32 | null | # Transferring Monolingual Model to Low-Resource Language: The Case Of Tigrinya:
## Proposed Method:
<img src="data/proposed.png" height = "330" width ="760" >
The proposed method transfers a mono-lingual Transformer model into new target language at lexical level by learning new token embeddings. All implementatio... |
CallumRai/HansardGPT2 | [
"pytorch",
"jax",
"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... | 14 | null | ruGPT-3 fine-tuned on russian fanfiction about Bangatan Boys (BTS). |
Cameron/BERT-eec-emotion | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"no_rep... | 36 | null | https://www.guilded.gg/thisiscineplex/overview/news/XRz48Dr6
https://www.guilded.gg/FLIXmasGR/overview/news/7R0WorPy
https://www.guilded.gg/FLIXmasGR/overview/news/NyE5BPmy
https://www.guilded.gg/FLIXmasGR/overview/news/2l3Konal
https://www.guilded.gg/FLIXmasGR/overview/news/AykDjvVR
https://www.guilded.gg/FLIXmasGR/ov... |
Cameron/BERT-jigsaw-identityhate | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
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"max_length": null
},
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"no_rep... | 37 | null | # ReviewBERT
BERT (post-)trained from review corpus to understand sentiment, options and various e-commence aspects.
`BERT-DK_laptop` is trained from 100MB laptop corpus under `Electronics/Computers & Accessories/Laptops`.
## Model Description
The original model is from `BERT-base-uncased` trained from Wikipedi... |
Cameron/BERT-jigsaw-severetoxic | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 30 | null | # ReviewBERT
BERT (post-)trained from review corpus to understand sentiment, options and various e-commence aspects.
`BERT-DK_rest` is trained from 1G (19 types) restaurants from Yelp.
## Model Description
The original model is from `BERT-base-uncased` trained from Wikipedia+BookCorpus.
Models are post-trained ... |
Cameron/BERT-mdgender-convai-binary | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 33 | null | # ReviewBERT
BERT (post-)trained from review corpus to understand sentiment, options and various e-commence aspects.
`BERT-DK_laptop` is trained from 100MB laptop corpus under `Electronics/Computers & Accessories/Laptops`.
`BERT-PT_*` addtionally uses SQuAD 1.1.
## Model Description
The original model is from ... |
Cameron/BERT-mdgender-convai-ternary | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 38 | null | # ReviewBERT
BERT (post-)trained from review corpus to understand sentiment, options and various e-commence aspects.
`BERT-DK_rest` is trained from 1G (19 types) restaurants from Yelp.
`BERT-PT_*` addtionally uses SQuAD 1.1.
## Model Description
The original model is from `BERT-base-uncased` trained from Wikipe... |
Cameron/BERT-mdgender-wizard | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 30 | null | # ReviewBERT
BERT (post-)trained from review corpus to understand sentiment, options and various e-commence aspects.
Please visit https://github.com/howardhsu/BERT-for-RRC-ABSA for details.
`BERT-XD_Review` is a cross-domain (beyond just `laptop` and `restaurant`) language model, where each example is from a sing... |
Cameron/BERT-rtgender-opgender-annotations | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 33 | null | # ReviewBERT
BERT (post-)trained from review corpus to understand sentiment, options and various e-commence aspects.
`BERT_Review` is cross-domain (beyond just `laptop` and `restaurant`) language model with one example from randomly mixed domains, post-trained (fine-tuned) on a combination of 5-core Amazon reviews ... |
Canadiancaleb/DialoGPT-small-walter | [
"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... | 13 | null | ---
language:
- pt
---
This model was distilled from [BERTimbau](https://huggingface.co/neuralmind/bert-base-portuguese-cased)
## Usage
```python
from transformers import AutoTokenizer # Or BertTokenizer
from transformers import AutoModelForPreTraining # Or BertForPreTraining for loading pretraining heads
from ... |
Canadiancaleb/jessebot | [] | null | {
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"num_beams... | 0 | null | ---
language:
- pt
---
Image Captioning in Portuguese trained with ViT and GPT2
[DEMO](https://huggingface.co/spaces/adalbertojunior/image_captioning_portuguese)
Research supported with Cloud TPUs from Google's TPU Research Cloud (TRC) |
Captain272/lstm | [] | null | {
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"num_beams... | 0 | null | This model has been trained by fine-tuning a BERTweet sentiment classification model named "finiteautomata/bertweet-base-sentiment-analysis", on a labeled positive/negative dataset of tweets.
email : adam.chellaoui@epfl.ch |
dccuchile/albert-base-spanish-finetuned-mldoc | [
"pytorch",
"albert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"AlbertForSequenceClassification"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"length_penalty": null,
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"min_length": null,
"no... | 34 | null | ---
title: Twitter Sentiments
emoji: 😍
colorFrom: yellow
colorTo: blue
sdk: streamlit
app_file: app.py
pinned: false
---
# Configuration
`title`: _string_
Display title for the Space
`emoji`: _string_
Space emoji (emoji-only character allowed)
`colorFrom`: _string_
Color for Thumbnail grad... |
dccuchile/albert-base-spanish-finetuned-pawsx | [
"pytorch",
"albert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"AlbertForSequenceClassification"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
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"no... | 25 | 2021-06-24T03:46:16Z | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- null
model_index:
- name: 100perc
results:
- task:
name: Causal Language Modeling
type: text-generation
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probabl... |
dccuchile/albert-xlarge-spanish-finetuned-ner | [
"pytorch",
"albert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"AlbertForTokenClassification"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 5 | null | ---
language:
- zh_CN
- zh_CN
license: mit
tags:
- generated_from_trainer
metrics:
- rouge
model_index:
- name: filter-mlsum-pretrained
results:
- task:
name: Translation
type: translation
metric:
name: Rouge1
type: rouge
value: 42.1802
---
<!-- This model card has been generated ... |
dccuchile/bert-base-spanish-wwm-uncased-finetuned-mldoc | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
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},
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"no_rep... | 39 | 2021-07-07T18:25:16Z | ---
language:
- zh_CN
- zh_CN
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- bleu
model_index:
- name: tmp
results:
- task:
name: Translation
type: translation
metric:
name: Bleu
type: bleu
value: 0.0099
---
<!-- This model card has been generated automatically acco... |
dccuchile/bert-base-spanish-wwm-uncased-finetuned-ner | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 5 | 2021-07-02T15:01:28Z | ---
license: mit
tags:
- generated_from_trainer
datasets:
- null
model_index:
- name: topicalchat-multiturn
results:
- task:
name: Causal Language Modeling
type: text-generation
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should ... |
CennetOguz/distilbert-base-uncased-finetuned-recipe-accelerate | [
"pytorch",
"distilbert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"DistilBertForMaskedLM"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"min_length": null,
"no_repea... | 7 | null | ## Usage
The model can be used directly (without a language model) as follows:
```python
import soundfile as sf
import torch
from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
import argparse
def parse_transcription(wav_file):
# load pretrained model
processor = Wav2Vec2Processor.from_pretrained("addy88... |
Chaewon/mnmt_decoder_en_gpt2 | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- itihasa
model-index:
- name: t5-base-finetuned-sn-to-en
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 comm... |
Chakita/Friends | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 8 | 2021-12-19T16:52:53Z | ## Usage
The model can be used directly (without a language model) as follows:
```python
import soundfile as sf
import torch
from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
import argparse
def parse_transcription(wav_file):
# load pretrained model
processor = Wav2Vec2Processor.from_pretrained("addy88... |
ChauhanVipul/BERT | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ## Usage
The model can be used directly (without a language model) as follows:
```python
import soundfile as sf
import torch
from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
import argparse
def parse_transcription(wav_file):
# load pretrained model
processor = Wav2Vec2Processor.from_pretrained("addy88... |
Venkatakrishnan-Ramesh/Text_gen | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# aditeyabaral/sentencetransformer-roberta-base
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and c... |
ComCom/gpt2-large | [
"pytorch",
"gpt2",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"GPT2Model"
],
"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": nul... | 1 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- conll2003
model-index:
- name: distilbert-base-uncased-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type: conll2003
args: conll2003
---
<!-- This mod... |
Contrastive-Tension/BERT-Distil-CT | [
"pytorch",
"tf",
"distilbert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"DistilBertForMaskedLM"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repea... | 9 | null | ---
tags:
- conversational
---
# Rick DialoGPT medium model |
Contrastive-Tension/BERT-Distil-NLI-CT | [
"pytorch",
"tf",
"distilbert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"DistilBertForMaskedLM"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repea... | 6 | null | distilbert-base-uncased finetuned on the conll2003 dataset for NER. |
Crasher222/kaggle-comp-test | [
"pytorch",
"bert",
"text-classification",
"en",
"dataset:Crasher222/autonlp-data-kaggle-test",
"transformers",
"autonlp",
"co2_eq_emissions"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 29 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-base-timit-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 remove this comment. -->
# wav2... |
Crumped/imdb-simpleRNN | [
"keras"
] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
language: en
tags:
- financial-sentiment-analysis
- sentiment-analysis
datasets:
- financial_phrasebank
widget:
- text: Operating profit rose to EUR 13.1 mn from EUR 8.7 mn in the corresponding period in 2007 representing 7.7 % of net sales.
- text: Bids or offers include at least 1,000 shares and the value of the ... |
Culmenus/opus-mt-de-is-finetuned-de-to-is_nr2-finetuned-de-to-is_nr2 | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type: conl... |
DaWang/demo | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-small-wikinewssum-test
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then rem... |
Darkrider/covidbert_mednli | [
"transformers"
] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 3 | null | ---
language: th
datasets:
- common_voice
tags:
- audio
- automatic-speech-recognition
- hf-asr-leaderboard
- robust-speech-event
- speech
- xlsr-fine-tuning
license: cc-by-sa-4.0
model-index:
- name: XLS-R-53 - Thai
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
... |
Darren/darren | [
"pytorch"
] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
widget:
- text: "สวนกุหลาบเป็นโรงเรียนอะไร"
context: "โรงเรียนสวนกุหลาบวิทยาลัย (Suankularb Wittayalai School) (อักษรย่อ : ส.ก. / S.K.) เป็นโรงเรียนชายล้วน ระดับชั้นมัธยมศึกษาขนาดใหญ่พิเศษ สังกัดสำนักงานเขตพื้นที่การศึกษามัธยมศึกษาเขต 1 สำนักงานคณะกรรมการการศึกษาขั้นพื้นฐาน (ชื่อเดิม: กรมสามัญศึกษา) กระทรวงศึกษาธ... |
DarshanDeshpande/marathi-distilbert | [
"pytorch",
"tf",
"distilbert",
"fill-mask",
"mr",
"dataset:Oscar Corpus, News, Stories",
"arxiv:1910.01108",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"DistilBertForMaskedLM"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repea... | 14 | null | # Finetuend `xlm-roberta-base` model on Thai sequence and token classification datasets
<br>
Finetuned XLM Roberta BASE model on Thai sequence and token classification datasets
The script and documentation can be found at [this repository](https://github.com/vistec-AI/thai2transformers).
<br>
## Model description
... |
DataikuNLP/average_word_embeddings_glove.6B.300d | [
"arxiv:1908.10084",
"sentence-transformers",
"feature-extraction",
"sentence-similarity",
"license:apache-2.0"
] | sentence-similarity | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
tags:
- conversational
---
# Michael Scott DialoGPT Model |
DataikuNLP/camembert-base | [
"pytorch",
"tf",
"camembert",
"fill-mask",
"fr",
"dataset:oscar",
"arxiv:1911.03894",
"transformers",
"license:mit",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"CamembertForMaskedLM"
],
"model_type": "camembert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_... | 8 | null | ---
tags:
- conversational
---
# Harry Potter DialoGPT Model |
Davlan/byt5-base-eng-yor-mt | [
"pytorch",
"t5",
"text2text-generation",
"arxiv:2103.08647",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"T5ForConditionalGeneration"
],
"model_type": "t5",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_n... | 11 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-xlsr-53-AL-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 remove this comment. -->
# wav... |
Davlan/byt5-base-yor-eng-mt | [
"pytorch",
"t5",
"text2text-generation",
"arxiv:2103.08647",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"T5ForConditionalGeneration"
],
"model_type": "t5",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_n... | 12 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-xlsr-53-AL
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. -->
# wav2vec2-... |
Davlan/distilbert-base-multilingual-cased-masakhaner | [
"pytorch",
"tf",
"distilbert",
"token-classification",
"arxiv:2103.11811",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"DistilBertForTokenClassification"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 16 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-xlsr-53-Total
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. -->
# wav2ve... |
Davlan/mt5_base_eng_yor_mt | [
"pytorch",
"mt5",
"text2text-generation",
"arxiv:2103.08647",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MT5ForConditionalGeneration"
],
"model_type": "mt5",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 2 | null | ---
language: "id"
widget:
- text: "dia orang yang baik ya bunds."
---
## how to use
```python
from transformers import pipeline, set_seed
path = "akahana/indonesia-emotion-roberta"
emotion = pipeline('text-classification',
model=path,device=0)
set_seed(42)
kalimat = "dia orang... |
Davlan/xlm-roberta-base-finetuned-naija | [
"pytorch",
"xlm-roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"XLMRobertaForMaskedLM"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repe... | 1 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-tamil-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 ... |
Davlan/xlm-roberta-large-masakhaner | [
"pytorch",
"tf",
"xlm-roberta",
"token-classification",
"arxiv:2103.11811",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"XLMRobertaForTokenClassification"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 1,449 | null |
---
language: en
datasets:
- cuad
---
# Model Card for RoBERTa Large Model fine-tuned with CUAD dataset
This model is the fine-tuned version of "RoBERTa Large" using CUAD dataset
# Model Details
## Model Description
The [Contract Understanding Atticus Dataset (CUAD)](https://www.atticusprojectai.org/c... |
Davlan/xlm-roberta-large-ner-hrl | [
"pytorch",
"tf",
"xlm-roberta",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"XLMRobertaForTokenClassification"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 1,322 | null | ---
language: tr
widget:
- text: "Mustafa Kemal Atatürk 19 Mayıs 1919'da Samsun'a çıktı."
---
# Turkish Named Entity Recognition (NER) Model
This model is the fine-tuned version of "xlm-roberta-base"
(a multilingual version of RoBERTa)
using a reviewed version of well known Turkish NER dataset
(https://github.com/ste... |
Declan/CNN_model_v3 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 3 | null | ---
language: "ar"
tags:
- text-generation
datasets:
- Arabic poetry from several eras
---
# GPT2-Small-Arabic-Poetry
## Model description
Fine-tuned model of Arabic poetry dataset based on gpt2-small-arabic.
## Intended uses & limitations
#### How to use
An example is provided in this [colab notebook](https://co... |
Declan/CNN_model_v5 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 3 | 2020-09-06T15:15:36Z | ---
tags:
- translation
language:
- ar
- en
license: mit
---
### mbart-large-ar-en
This is mbart-large-cc25, finetuned on a subset of the OPUS corpus for ar_en.
Usage: see [example notebook](https://colab.research.google.com/drive/1I6RFOWMaTpPBX7saJYjnSTddW0TD6H1t?usp=sharing)
Note: model has limited training se... |
Declan/FoxNews_model_v1 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 3 | null | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: conserv_fulltext_model
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. -->
# conserv_fulltext_mo... |
Declan/FoxNews_model_v8 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 3 | null | This is a copy of: https://huggingface.co/hf-internal-testing/tiny-random-gpt2
Changes: use old format for `pytorch_model.bin`.
|
Declan/HuffPost_model_v1 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 3 | null | This is a copy of: https://huggingface.co/hf-internal-testing/tiny-random-mbart
Changes: use old format for `pytorch_model.bin`.
|
Declan/HuffPost_model_v2 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 3 | null | This is a copy of: https://huggingface.co/hf-internal-testing/tiny-random-mpnet
Changes: use old format for `pytorch_model.bin`.
|
Declan/HuffPost_model_v4 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 3 | null | This is a copy of: https://huggingface.co/hf-internal-testing/tiny-random-xlnet
Changes: use old format for `pytorch_model.bin`.
|
Declan/HuffPost_model_v8 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 7 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- matthews_correlation
model_index:
- name: distilbert-base-uncased-finetuned-cola
results:
- task:
name: Text Classification
type: text-classification
metric:
name: Matthews Correlation
type: matthews_correlation
valu... |
Declan/NPR_model_v2 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 7 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-cloud-ner
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proof... |
Declan/NPR_model_v3 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 9 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-cloud1-ner
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proo... |
Declan/NPR_model_v4 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 3 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-cloud2-ner
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proo... |
Declan/NPR_model_v6 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 3 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-ner
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread a... |
Declan/WallStreetJournal_model_v2 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 7 | null | ---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
datasets:
- alecmullen/autonlp-data-group-classification
co2_eq_emissions: 0.4362732160754736
---
# Model Trained Using AutoNLP
- Problem type: Multi-class Classification
- Model ID: 441411446
- CO2 Emissions (in grams): 0.4362732160754736
## Validat... |
DeltaHub/adapter_t5-3b_mrpc | [
"pytorch",
"transformers"
] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 3 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wmt16
model-index:
- name: t5-small-finetuned300-en-to-de
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this co... |
DeltaHub/lora_t5-base_mrpc | [
"pytorch",
"transformers"
] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 3 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wmt16
model-index:
- name: t5-small-finetuned8-en-to-de
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 comm... |
Deniskin/essays_small_2000 | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
language:
- ru
multilinguality:
- monolingual
widget:
- text: "Жалобы на боль внизу <mask> после приёма пищи."
example_title: "pain_example"
- text: "Пациентка наблюдалась у <mask> по поводу грибкового поражения кожи."
example_title: "spec_example"
- text: "Появился зуд тела, <mask> веса, потливость, проводил к... |
Deniskin/gpt3_medium | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"has_space"
] | 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... | 52 | null | ---
language:
- ar
- dz
tags:
- pytorch
- bert
- multilingual
- ar
- dz
license: apache-2.0
widget:
- text: " أنا من الجزائر من ولاية [MASK] "
- text: "rabi [MASK] khouya sami"
- text: " ربي [MASK] خويا لعزيز"
- text: "tahya el [MASK]."
- text: "rouhi ya dzayer [MASK]"
inference: true
---
<img src="https://raw.gi... |
DeskDown/MarianMixFT_en-vi | [
"pytorch",
"marian",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MarianMTModel"
],
"model_type": "marian",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 5 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-uncased_token_itr0_0.0001_all_01_03_2022-04_48_27
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
shoul... |
Devid/DialoGPT-small-Miku | [
"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... | 10 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: correct_BERT_token_itr0_0.0001_editorials_01_03_2022-15_50_21
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
sho... |
Devmapall/paraphrase-quora | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"T5ForConditionalGeneration"
],
"model_type": "t5",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": true,
"length_penalty": 2,
"max_length": 200,
"min_length": 30,
"no_repeat_ngram_s... | 3 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: correct_BERT_token_itr0_0.0001_essays_01_03_2022-15_48_47
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should ... |
Devrim/prism-default | [
"license:mit"
] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: correct_BERT_token_itr0_0.0001_webDiscourse_01_03_2022-15_47_14
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
s... |
DevsIA/Devs_IA | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: correct_distilBERT_token_itr0_1e-05_all_01_03_2022-15_43_47
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
shoul... |
DevsIA/imagenes | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: correct_distilBERT_token_itr0_1e-05_editorials_01_03_2022-15_42_32
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. Yo... |
DewiBrynJones/wav2vec2-large-xlsr-welsh | [
"cy",
"dataset:common_voice",
"audio",
"automatic-speech-recognition",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: correct_distilBERT_token_itr0_1e-05_essays_01_03_2022-15_41_29
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
sh... |
DheerajPranav/Dialo-GPT-Rick-bot | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: correct_distilBERT_token_itr0_1e-05_webDiscourse_01_03_2022-15_40_24
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. ... |
Dhito/am | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2022-03-01T14:36:14Z | ---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: correct_twitter_RoBERTa_token_itr0_1e-05_all_01_03_2022-15_36_04
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proo... |
Dhruva/Interstellar | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: correct_twitter_RoBERTa_token_itr0_1e-05_essays_01_03_2022-15_32_16
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably p... |
Dibyaranjan/nl_image_search | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: correct_twitter_RoBERTa_token_itr0_1e-05_webDiscourse_01_03_2022-15_30_39
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should prob... |
DicoTiar/wisdomfiy | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 3 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilBERT_token_itr0_0.0001_all_01_03_2022-15_22_12
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should proba... |
DiegoBalam12/institute_classification | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilBERT_token_itr0_0.0001_essays_01_03_2022-15_18_35
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should pr... |
Digakive/Hsgshs | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilBERT_token_itr0_0.0001_webDiscourse_01_03_2022-15_16_57
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
sho... |
Dilmk2/DialoGPT-small-harrypotter | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 13 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilBERT_token_itr0_1e-05_all_01_03_2022-15_14_04
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probab... |
DimaOrekhov/transformer-method-name | [
"pytorch",
"encoder-decoder",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 8 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilBERT_token_itr0_1e-05_essays_01_03_2022-15_11_44
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should pro... |
Dimedrolza/DialoGPT-small-cyberpunk | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 9 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilBERT_token_itr0_1e-05_webDiscourse_01_03_2022-15_10_39
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
shou... |
Dmitry12/sber | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert_token_itr0_1e-05_all_01_03_2022-14_33_33
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probab... |
DongHyoungLee/distilbert-base-uncased-finetuned-cola | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:glue",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | {
"architectures": [
"DistilBertForSequenceClassification"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 27 | 2022-02-27T18:11:24Z | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: finetuned_sentence_itr0_0.0002_all_27_02_2022-19_11_17
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and c... |
Donghyun/L2_BERT | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: finetuned_sentence_itr0_0.0002_editorials_27_02_2022-19_42_36
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofrea... |
Dongjae/mrc2reader | [
"pytorch",
"xlm-roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"XLMRobertaForQuestionAnswering"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 3 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: finetuned_sentence_itr0_0.0002_essays_27_02_2022-19_33_10
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread an... |
Dongmin/testmodel | [
"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... | 11 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: finetuned_sentence_itr0_0.0002_webDiscourse_27_02_2022-19_25_06
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofr... |
Waynehillsdev/Wayne_NLP_mT5 | [
"pytorch",
"tensorboard",
"mt5",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MT5ForConditionalGeneration"
],
"model_type": "mt5",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 11 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: finetuned_sentence_itr0_1e-05_all_01_03_2022-13_25_32
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should prob... |
Waynehillsdev/wav2vec2-base-timit-demo-colab | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"transformers",
"generated_from_trainer",
"license:apache-2.0"
] | automatic-speech-recognition | {
"architectures": [
"Wav2Vec2ForCTC"
],
"model_type": "wav2vec2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_s... | 5 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: finetuned_sentence_itr0_2e-05_all_01_03_2022-13_11_55
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should prob... |
Doohae/p_encoder | [
"pytorch"
] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 3 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: finetuned_sentence_itr0_2e-05_all_26_02_2022-03_57_45
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and co... |
Doohae/roberta | [
"pytorch",
"roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"RobertaForQuestionAnswering"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 3 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: finetuned_sentence_itr0_2e-05_all_27_02_2022-19_05_42
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and co... |
albert-base-v1 | [
"pytorch",
"tf",
"safetensors",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"transformers",
"exbert",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"AlbertForMaskedLM"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_... | 38,156 | 2022-02-27T17:07:05Z | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: finetuned_sentence_itr2_0.0002_all_27_02_2022-18_06_59
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and c... |
albert-base-v2 | [
"pytorch",
"tf",
"jax",
"rust",
"safetensors",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"AlbertForMaskedLM"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_... | 4,785,283 | 2022-02-26T03:09:07Z | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: finetuned_sentence_itr2_2e-05_all_26_02_2022-04_09_01
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and co... |
albert-large-v1 | [
"pytorch",
"tf",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"AlbertForMaskedLM"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_... | 687 | 2022-02-27T16:39:04Z | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: finetuned_sentence_itr2_2e-05_all_27_02_2022-17_38_58
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and co... |
albert-large-v2 | [
"pytorch",
"tf",
"safetensors",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"AlbertForMaskedLM"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_... | 26,792 | 2022-02-27T17:56:36Z | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: finetuned_sentence_itr2_2e-05_webDiscourse_27_02_2022-18_56_32
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofre... |
albert-xlarge-v1 | [
"pytorch",
"tf",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"AlbertForMaskedLM"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_... | 341 | 2022-02-27T17:35:08Z | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: finetuned_sentence_itr2_3e-05_all_27_02_2022-18_35_02
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and co... |
albert-xlarge-v2 | [
"pytorch",
"tf",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"AlbertForMaskedLM"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_... | 2,973 | 2022-02-27T17:12:41Z | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: finetuned_sentence_itr3_0.0002_all_27_02_2022-18_12_34
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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