index int64 0 22.3k | modelId stringlengths 8 111 | label list | readme stringlengths 0 385k |
|---|---|---|---|
984 | ethanyt/guwen-sent | [
"Neg",
"ImpNeg",
"Nerual",
"ImpPos",
"Pos"
] | ---
language:
- "zh"
thumbnail: "https://user-images.githubusercontent.com/9592150/97142000-cad08e00-179a-11eb-88df-aff9221482d8.png"
tags:
- "chinese"
- "classical chinese"
- "literary chinese"
- "ancient chinese"
- "bert"
- "pytorch"
- "sentiment classificatio"
license: "apache-2.0"
pipeline_tag: "text-classificatio... |
985 | evandrodiniz/autonlp-api-boamente-417310788 | [
"negative",
"positive"
] | ---
tags: autonlp
language: unk
widget:
- text: "I love AutoNLP 🤗"
datasets:
- evandrodiniz/autonlp-data-api-boamente
co2_eq_emissions: 6.826886567147602
---
# Model Trained Using AutoNLP
- Problem type: Binary Classification
- Model ID: 417310788
- CO2 Emissions (in grams): 6.826886567147602
## Validation Metrics
... |
986 | evandrodiniz/autonlp-api-boamente-417310793 | [
"negative",
"positive"
] | ---
tags: autonlp
language: unk
widget:
- text: "I love AutoNLP 🤗"
datasets:
- evandrodiniz/autonlp-data-api-boamente
co2_eq_emissions: 9.446754273734577
---
# Model Trained Using AutoNLP
- Problem type: Binary Classification
- Model ID: 417310793
- CO2 Emissions (in grams): 9.446754273734577
## Validation Metrics
... |
988 | fabriceyhc/bert-base-uncased-ag_news | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
- sibyl
datasets:
- ag_news
metrics:
- accuracy
model-index:
- name: bert-base-uncased-ag_news
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: ag_news
type: ag_news
args: default
metrics:... |
989 | fabriceyhc/bert-base-uncased-amazon_polarity | [
"negative",
"positive"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
- sibyl
datasets:
- amazon_polarity
metrics:
- accuracy
model-index:
- name: bert-base-uncased-amazon_polarity
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: amazon_polarity
type: amazon_polarity
... |
990 | fabriceyhc/bert-base-uncased-dbpedia_14 | [
"LABEL_0",
"LABEL_1",
"LABEL_10",
"LABEL_11",
"LABEL_12",
"LABEL_13",
"LABEL_2",
"LABEL_3",
"LABEL_4",
"LABEL_5",
"LABEL_6",
"LABEL_7",
"LABEL_8",
"LABEL_9"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
- sibyl
datasets:
- dbpedia_14
metrics:
- accuracy
model-index:
- name: bert-base-uncased-dbpedia_14
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: dbpedia_14
type: dbpedia_14
args: dbpedia_... |
991 | fabriceyhc/bert-base-uncased-imdb | [
"neg",
"pos"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
- sibyl
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: bert-base-uncased-imdb
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
args: plain_text
metrics:
- na... |
992 | fabriceyhc/bert-base-uncased-yahoo_answers_topics | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4",
"LABEL_5",
"LABEL_6",
"LABEL_7",
"LABEL_8",
"LABEL_9"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
- sibyl
datasets:
- yahoo_answers_topics
metrics:
- accuracy
model-index:
- name: bert-base-uncased-yahoo_answers_topics
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: yahoo_answers_topics
type: y... |
994 | facebook/bart-large-mnli | [
"contradiction",
"entailment",
"neutral"
] | ---
license: mit
thumbnail: https://huggingface.co/front/thumbnails/facebook.png
pipeline_tag: zero-shot-classification
datasets:
- multi_nli
---
# bart-large-mnli
This is the checkpoint for [bart-large](https://huggingface.co/facebook/bart-large) after being trained on the [MultiNLI (MNLI)](https://huggingface.co/da... |
995 | fadhilarkan/distilbert-base-uncased-finetuned-cola-3 | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- matthews_correlation
model-index:
- name: distilbert-base-uncased-finetuned-cola-3
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete... |
996 | fadhilarkan/distilbert-base-uncased-finetuned-cola-4 | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- matthews_correlation
model-index:
- name: distilbert-base-uncased-finetuned-cola-4
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete... |
997 | fadhilarkan/distilbert-base-uncased-finetuned-cola | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- matthews_correlation
model-index:
- name: distilbert-base-uncased-finetuned-cola
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete i... |
1,004 | fergusq/finbert-finnsentiment | [
"NEGATIVE",
"NEUTRAL",
"POSITIVE"
] | ---
language: fi
license: cc-by-4.0
---
# FinBERT fine-tuned with the FinnSentiment dataset
This is a FinBERT model fine-tuned with the [FinnSentiment dataset](https://arxiv.org/pdf/2012.02613.pdf). 90% of sentences were used for training and 10% for evaluation.
## Evaluation results
|Metric|Score|
|--|--|
|Accurac... |
1,005 | ffalcao/distilbert-base-uncased-finetuned-emotion | [
"sadness",
"joy",
"love",
"anger",
"fear",
"surprise"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: split
... |
1,006 | fgaim/tielectra-small-sentiment | [
"NEGATIVE",
"POSITIVE"
] | ---
language: ti
widget:
- text: "ድምጻዊ ኣብርሃም ኣፈወርቂ ንዘልኣለም ህያው ኮይኑ ኣብ ልብና ይነብር"
metrics:
- f1
- precision
- recall
- accuracy
model-index:
- name: tielectra-small-sentiment
results:
- task:
name: Text Classification
type: text-classification
metrics:
- name: F1
type: f1
value: 0.82289... |
1,007 | fgaim/tiroberta-sentiment | [
"NEGATIVE",
"POSITIVE"
] | ---
language: ti
widget:
- text: "ድምጻዊ ኣብርሃም ኣፈወርቂ ንዘልኣለም ህያው ኮይኑ ኣብ ልብና ይነብር"
datasets:
- TLMD
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: tiroberta-sentiment
results:
- task:
name: Text Classification
type: text-classification
metrics:
- name: Accuracy
type: accura... |
1,009 | finiteautomata/bertweet-base-emotion-analysis | [
"anger",
"disgust",
"fear",
"joy",
"others",
"sadness",
"surprise"
] | ---
language:
- en
tags:
- emotion-analysis
---
# Emotion Analysis in English
## bertweet-base-emotion-analysis
Repository: [https://github.com/finiteautomata/pysentimiento/](https://github.com/finiteautomata/pysentimiento/)
Model trained with EmoEvent corpus for Emotion detection in English. Base model is [B... |
1,010 | finiteautomata/bertweet-base-sentiment-analysis | [
"NEG",
"NEU",
"POS"
] | ---
language:
- en
tags:
- sentiment-analysis
---
# Sentiment Analysis in English
## bertweet-sentiment-analysis
Repository: [https://github.com/finiteautomata/pysentimiento/](https://github.com/finiteautomata/pysentimiento/)
Model trained with SemEval 2017 corpus (around ~40k tweets). Base model is [BERTweet... |
1,011 | finiteautomata/beto-emotion-analysis | [
"anger",
"disgust",
"fear",
"joy",
"others",
"sadness",
"surprise"
] | ---
language:
- es
tags:
- emotion-analysis
---
# Emotion Analysis in Spanish
## beto-emotion-analysis
Repository: [https://github.com/finiteautomata/pysentimiento/](https://github.com/finiteautomata/pysentimiento/)
Model trained with TASS 2020 Task 2 corpus for Emotion detection in Spanish. Base model is [B... |
1,012 | finiteautomata/beto-headlines-sentiment-analysis | [
"NEG",
"NEU",
"POS"
] | # Targeted Sentiment Analysis in News Headlines
BERT classifier fine-tuned in a news headlines dataset annotated for target polarity.
(details to be published)
## Examples
Input is as follows
`Headline [SEP] Target`
where headline is the news title and target is an entity present in the headline.
Try
`Alberto ... |
1,013 | finiteautomata/beto-sentiment-analysis | [
"NEG",
"NEU",
"POS"
] | ---
language:
- es
tags:
- sentiment-analysis
---
# Sentiment Analysis in Spanish
## beto-sentiment-analysis
**NOTE: this model will be removed soon -- use [pysentimiento/robertuito-sentiment-analysis](https://huggingface.co/pysentimiento/robertuito-sentiment-analysis) instead**
Repository: [https://github.com/... |
1,016 | flax-community/bert-swahili-news-classification | [
"afya",
"burudani",
"kimataifa",
"kitaifa",
"michezo",
"uchumi"
] | ---
language: sw
widget:
- text: "Idris ameandika kwenye ukurasa wake wa Instagram akimkumbusha Diamond kutekeleza ahadi yake kumpigia Zari magoti kumuomba msamaha kama alivyowahi kueleza awali.Idris ameandika;"
datasets:
- flax-community/swahili-safi
---
## Swahili News Classification with BERT
This model was traine... |
1,017 | flax-community/clip-vision-bert-vqa-ft-6k | [
"<unk>",
"0",
"000",
"1",
"1 4",
"1 foot",
"1 hour",
"1 in back",
"1 in front",
"1 in middle",
"1 inch",
"1 on left",
"1 on right",
"1 way",
"1 world",
"1 year",
"1.00",
"10",
"10 feet",
"10 inches",
"10 years",
"100",
"100 feet",
"100 year party ct",
"1000",
"101",... | # CLIP-Vision-BERT Multilingual VQA Model
Fine-tuned CLIP-Vision-BERT on translated [VQAv2](https://visualqa.org/challenge.html) image-text pairs using sequence classification objective. We translate the dataset to three other languages other than English: French, German, and Spanish using the [MarianMT Models](https:... |
1,018 | flax-community/roberta-swahili-news-classification | [
"afya",
"burudani",
"kimataifa",
"kitaifa",
"michezo",
"uchumi"
] | ---
language: sw
widget:
- text: "Idris ameandika kwenye ukurasa wake wa Instagram akimkumbusha Diamond kutekeleza ahadi yake kumpigia Zari magoti kumuomba msamaha kama alivyowahi kueleza awali.Idris ameandika;"
datasets:
- flax-community/swahili-safi
---
## Swahili News Classification with RoBERTa
This model was tr... |
1,019 | fnlp/cpt-large | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | ---
tags:
- fill-mask
- text2text-generation
- fill-mask
- text-classification
- Summarization
- Chinese
- CPT
- BART
- BERT
- seq2seq
language: zh
---
# Chinese CPT-Large
### News
**12/30/2022**
An updated version of CPT & Chinese BART are released. In the new version, we changed the following parts:
- **Vocabul... |
1,020 | frahman/distilbert-base-uncased-distilled-clinc | [
"accept_reservations",
"account_blocked",
"alarm",
"application_status",
"apr",
"are_you_a_bot",
"balance",
"bill_balance",
"bill_due",
"book_flight",
"book_hotel",
"calculator",
"calendar",
"calendar_update",
"calories",
"cancel",
"cancel_reservation",
"car_rental",
"card_declin... | ---
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
... |
1,021 | frahman/distilbert-base-uncased-finetuned-clinc | [
"accept_reservations",
"account_blocked",
"alarm",
"application_status",
"apr",
"are_you_a_bot",
"balance",
"bill_balance",
"bill_due",
"book_flight",
"book_hotel",
"calculator",
"calendar",
"calendar_update",
"calories",
"cancel",
"cancel_reservation",
"car_rental",
"card_declin... | ---
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
... |
1,022 | frahman/distilbert-base-uncased-finetuned-emotion | [
"sadness",
"joy",
"love",
"anger",
"fear",
"surprise"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: default... |
1,024 | gagandeepkundi/latam-question-quality | [
"High Quality",
"Low Quality"
] | ---
tags: autonlp
language: es
widget:
- text: "I love AutoNLP 🤗"
datasets:
- gagandeepkundi/autonlp-data-text-classification
co2_eq_emissions: 20.790169878009916
---
# Model Trained Using AutoNLP
- Problem type: Binary Classification
- Model ID: 19984005
- CO2 Emissions (in grams): 20.790169878009916
## Validation... |
1,025 | ganeshkharad/gk-hinglish-sentiment | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | ---
language:
- hi-en
tags:
- sentiment
- multilingual
- hindi codemix
- hinglish
license: apache-2.0
datasets:
- sail
---
# Sentiment Classification for hinglish text: `gk-hinglish-sentiment`
## Model description
Trained small amount of reviews dataset
## Intended uses & limitations
I wanted something to work w... |
1,027 | gbade786/distilbert-base-uncased-finetuned-emotion | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4",
"LABEL_5"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: default... |
1,028 | gchhablani/bert-base-cased-finetuned-cola | [
"acceptable",
"unacceptable"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
- fnet-bert-base-comparison
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: bert-base-cased-finetuned-cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE COLA
... |
1,029 | gchhablani/bert-base-cased-finetuned-mnli | [
"contradiction",
"entailment",
"neutral"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
- fnet-bert-base-comparison
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert-base-cased-finetuned-mnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MNLI
type: g... |
1,030 | gchhablani/bert-base-cased-finetuned-mrpc | [
"equivalent",
"not_equivalent"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
- fnet-bert-base-comparison
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert-base-cased-finetuned-mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
ty... |
1,031 | gchhablani/bert-base-cased-finetuned-qnli | [
"entailment",
"not_entailment"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
- fnet-bert-base-comparison
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert-base-cased-finetuned-qnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE QNLI
type: g... |
1,032 | gchhablani/bert-base-cased-finetuned-qqp | [
"duplicate",
"not_duplicate"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
- fnet-bert-base-comparison
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert-base-cased-finetuned-qqp
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE QQP
type... |
1,033 | gchhablani/bert-base-cased-finetuned-rte | [
"entailment",
"not_entailment"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
- fnet-bert-base-comparison
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert-base-cased-finetuned-rte
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE RTE
type: glu... |
1,034 | gchhablani/bert-base-cased-finetuned-sst2 | [
"negative",
"positive"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
- fnet-bert-base-comparison
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert-base-cased-finetuned-sst2
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE SST2
type: g... |
1,035 | gchhablani/bert-base-cased-finetuned-stsb | [
"LABEL_0"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
- fnet-bert-base-comparison
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: bert-base-cased-finetuned-stsb
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE STSB
type: ... |
1,036 | gchhablani/bert-base-cased-finetuned-wnli | [
"entailment",
"not_entailment"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
- fnet-bert-base-comparison
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert-base-cased-finetuned-wnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE WNLI
type: g... |
1,037 | gchhablani/bert-large-cased-finetuned-cola | [
"acceptable",
"unacceptable"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: bert-large-cased-finetuned-cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE COLA
type: glue
args:... |
1,038 | gchhablani/bert-large-cased-finetuned-mrpc | [
"equivalent",
"not_equivalent"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert-large-cased-finetuned-mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
type: glue
args: mrpc
... |
1,039 | gchhablani/bert-large-cased-finetuned-rte | [
"entailment",
"not_entailment"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert-large-cased-finetuned-rte
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE RTE
type: glue
args: rte
metri... |
1,040 | gchhablani/bert-large-cased-finetuned-wnli | [
"entailment",
"not_entailment"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert-large-cased-finetuned-wnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE WNLI
type: glue
args: wnli
me... |
1,041 | gchhablani/fnet-base-finetuned-cola | [
"acceptable",
"unacceptable"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
- fnet-bert-base-comparison
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: fnet-base-finetuned-cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE COLA
t... |
1,042 | gchhablani/fnet-base-finetuned-mnli | [
"contradiction",
"entailment",
"neutral"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
- fnet-bert-base-comparison
datasets:
- glue
metrics:
- accuracy
model-index:
- name: fnet-base-finetuned-mnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MNLI
type: glue
... |
1,043 | gchhablani/fnet-base-finetuned-mrpc | [
"equivalent",
"not_equivalent"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
- fnet-bert-base-comparison
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: fnet-base-finetuned-mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
type: gl... |
1,044 | gchhablani/fnet-base-finetuned-qnli | [
"entailment",
"not_entailment"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
- fnet-bert-base-comparison
datasets:
- glue
metrics:
- accuracy
model-index:
- name: fnet-base-finetuned-qnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE QNLI
type: glue
... |
1,045 | gchhablani/fnet-base-finetuned-qqp | [
"duplicate",
"not_duplicate"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
- fnet-bert-base-comparison
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: fnet-base-finetuned-qqp
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE QQP
type: glue... |
1,046 | gchhablani/fnet-base-finetuned-rte | [
"entailment",
"not_entailment"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
- fnet-bert-base-comparison
datasets:
- glue
metrics:
- accuracy
model-index:
- name: fnet-base-finetuned-rte
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE RTE
type: glue
... |
1,047 | gchhablani/fnet-base-finetuned-sst2 | [
"negative",
"positive"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
- fnet-bert-base-comparison
datasets:
- glue
metrics:
- accuracy
model-index:
- name: fnet-base-finetuned-sst2
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE SST2
type: glue
... |
1,048 | gchhablani/fnet-base-finetuned-stsb | [
"LABEL_0"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
- fnet-bert-base-comparison
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: fnet-base-finetuned-stsb
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE STSB
type: glue
... |
1,049 | gchhablani/fnet-base-finetuned-wnli | [
"entailment",
"not_entailment"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
- fnet-bert-base-comparison
datasets:
- glue
metrics:
- accuracy
model-index:
- name: fnet-base-finetuned-wnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE WNLI
type: glue
... |
1,050 | gchhablani/fnet-large-finetuned-cola-copy | [
"acceptable",
"unacceptable"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: fnet-large-finetuned-cola-copy
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE COLA
type: glue
args: ... |
1,051 | gchhablani/fnet-large-finetuned-cola-copy2 | [
"acceptable",
"unacceptable"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: fnet-large-finetuned-cola-copy2
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE COLA
type: glue
args:... |
1,052 | gchhablani/fnet-large-finetuned-cola-copy3 | [
"acceptable",
"unacceptable"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: fnet-large-finetuned-cola-copy3
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE COLA
type: glue
args:... |
1,053 | gchhablani/fnet-large-finetuned-cola-copy4 | [
"acceptable",
"unacceptable"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: fnet-large-finetuned-cola-copy4
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE COLA
type: glue
args:... |
1,054 | gchhablani/fnet-large-finetuned-cola | [
"acceptable",
"unacceptable"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: fnet-large-finetuned-cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE COLA
type: glue
args: cola
... |
1,055 | gchhablani/fnet-large-finetuned-mrpc | [
"equivalent",
"not_equivalent"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: fnet-large-finetuned-mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
type: glue
args: mrpc
met... |
1,056 | gchhablani/fnet-large-finetuned-qqp | [
"duplicate",
"not_duplicate"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: fnet-large-finetuned-qqp
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE QQP
type: glue
args: qqp
metric... |
1,057 | gchhablani/fnet-large-finetuned-rte | [
"entailment",
"not_entailment"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: fnet-large-finetuned-rte
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE RTE
type: glue
args: rte
metrics:
... |
1,058 | gchhablani/fnet-large-finetuned-sst2 | [
"negative",
"positive"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: fnet-large-finetuned-sst2
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE SST2
type: glue
args: sst2
metrics:... |
1,059 | gchhablani/fnet-large-finetuned-stsb | [
"LABEL_0"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: fnet-large-finetuned-stsb
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE STSB
type: glue
args: stsb
metrics... |
1,060 | gchhablani/fnet-large-finetuned-wnli | [
"entailment",
"not_entailment"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: fnet-large-finetuned-wnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE WNLI
type: glue
args: wnli
metrics:... |
1,070 | gurkan08/bert-turkish-text-classification | [
"ekonomi",
"spor",
"saglik",
"kultur_sanat",
"bilim_teknoloji",
"egitim"
] | ---
language: tr
---
# Turkish News Text Classification
Turkish text classification model obtained by fine-tuning the Turkish bert model (dbmdz/bert-base-turkish-cased)
# Dataset
Dataset consists of 11 classes were obtained from https://www.trthaber.com/. The model was created using the most distinctive 6 classe... |
1,075 | hd10/semeval2020_task11_tc | [
"Appeal_to_Authority",
"Appeal_to_fear-prejudice",
"Bandwagon,Reductio_ad_hitlerum",
"Black-and-White_Fallacy",
"Causal_Oversimplification",
"Doubt",
"Exaggeration,Minimisation",
"Flag-Waving",
"Loaded_Language",
"Name_Calling,Labeling",
"Repetition",
"Slogans",
"Thought-terminating_Cliches"... | Technique Classification for https://propaganda.qcri.org/ptc/index.html |
1,076 | hectorcotelo/autonlp-spanish_songs-202661 | [
"average",
"bad",
"good",
"hit",
"worst"
] | ---
tags: autonlp
language: es
widget:
- text: "Y si me tomo una cerveza
Vuelves a mi cabeza
Y empiezo a recordarte
Es que me gusta cómo besas
Con tu delicadeza
Puede ser que
Tú y yo, somos el uno para el otro
Que no dejo de pensarte
Quise olvidarte y tomé un poco
Y resultó extrañarte, yeah"
datasets:
- hectorcotelo/au... |
1,077 | hemekci/off_detection_turkish | [
"not offensive",
"offensive"
] | ---
language: tr
widget:
- text: "sevelim sevilelim bu dunya kimseye kalmaz"
---
## Offensive Language Detection Model in Turkish
- uses Bert and pytorch
- fine tuned with Twitter data.
- UTF-8 configuration is done
### Training Data
Number of training sentences: 31,277
**Example Tweets**
- 19823 Daliaan yifn... |
1,081 | huggingface/CodeBERTa-language-id | [
"go",
"java",
"javascript",
"php",
"python",
"ruby"
] | ---
language: code
thumbnail: https://cdn-media.huggingface.co/CodeBERTa/CodeBERTa.png
datasets:
- code_search_net
---
# CodeBERTa-language-id: The World’s fanciest programming language identification algo 🤯
To demonstrate the usefulness of our CodeBERTa pretrained model on downstream tasks beyond language modeling... |
1,083 | ibraheemmoosa/xlmindic-base-multiscript-soham | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4",
"LABEL_5"
] | ---
language:
- as
- bn
- gu
- hi
- mr
- ne
- or
- pa
- si
- sa
- bpy
- bh
- gom
- mai
license: apache-2.0
datasets:
- oscar
tags:
- multilingual
- albert
- fill-mask
- xlmindic
- nlp
- indoaryan
- indicnlp
- iso15919
- text-classification
widget:
- text : 'চীনের মধ্যাঞ্চলে আরও একটি শহরের বাসিন্দারা আবার ঘরবন্দী হয়ে পড়... |
1,084 | ibraheemmoosa/xlmindic-base-uniscript-soham | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4",
"LABEL_5"
] | ---
language:
- as
- bn
- gu
- hi
- mr
- ne
- or
- pa
- si
- sa
- bpy
- mai
- bh
- gom
license: apache-2.0
datasets:
- oscar
tags:
- multilingual
- albert
- xlmindic
- nlp
- indoaryan
- indicnlp
- iso15919
- transliteration
- text-classification
widget:
- text : 'cīnēra madhyāñcalē āraō ēkaṭi śaharēra bāsindārā ābāra g... |
1,085 | idjotherwise/autonlp-reading_prediction-172506 | [
"target"
] | ---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
datasets:
- idjotherwise/autonlp-data-reading_prediction
---
# Model Trained Using AutoNLP
- Problem type: Single Column Regression
- Model ID: 172506
## Validation Metrics
- Loss: 0.03257797285914421
- MSE: 0.03257797285914421
- MAE: 0.142465323209... |
1,086 | idrimadrid/autonlp-creator_classifications-4021083 | [
"ABC Studios",
"Blizzard Entertainment",
"Capcom",
"Cartoon Network",
"Clive Barker",
"DC Comics",
"Dark Horse Comics",
"Disney",
"Dreamworks",
"George Lucas",
"George R. R. Martin",
"Hanna-Barbera",
"HarperCollins",
"Hasbro",
"IDW Publishing",
"Ian Fleming",
"Icon Comics",
"Image ... | ---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
datasets:
- idrimadrid/autonlp-data-creator_classifications
---
# Model Trained Using AutoNLP
- Problem type: Multi-class Classification
- Model ID: 4021083
## Validation Metrics
- Loss: 0.6848716735839844
- Accuracy: 0.8825910931174089
- Macro F1: ... |
1,088 | doyoungkim/bert-base-uncased-finetuned-sst2 | [
"negative",
"positive"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model_index:
- name: bert-base-uncased-finetuned-sst2
results:
- dataset:
name: glue
type: glue
args: sst2
metric:
name: Accuracy
type: accuracy
value: 0.926605504587156
---
<!-- This... |
1,091 | imzachjohnson/autonlp-spinner-check-16492731 | [
"0",
"1"
] | ---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
datasets:
- imzachjohnson/autonlp-data-spinner-check
---
# Model Trained Using AutoNLP
- Problem type: Binary Classification
- Model ID: 16492731
## Validation Metrics
- Loss: 0.21610039472579956
- Accuracy: 0.9155366722657816
- Precision: 0.9530714... |
1,092 | inovex/multi2convai-corona-de-bert | [
"corona.traffic",
"corona.supplies",
"corona.quarantine",
"corona.masks",
"corona.illness",
"corona.package",
"corona.vaccine",
"corona.rumors",
"corona.risk",
"corona.course",
"corona.symptoms",
"corona.patients",
"corona.deathRate",
"corona.infect",
"corona.protect",
"corona.definiti... | ---
tags:
- text-classification
- pytorch
- transformers
widget:
- text: "Muss ich eine Maske tragen?"
license: mit
language: de
---
# Multi2ConvAI-Corona: finetuned Bert for German
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Corona (more details about our u... |
1,093 | inovex/multi2convai-corona-en-bert | [
"corona.traffic",
"corona.supplies",
"corona.quarantine",
"corona.masks",
"corona.illness",
"corona.package",
"corona.vaccine",
"corona.rumors",
"corona.risk",
"corona.course",
"corona.symptoms",
"corona.patients",
"corona.deathRate",
"corona.infect",
"corona.protect",
"corona.definiti... | ---
tags:
- text-classification
- pytorch
- transformers
widget:
- text: "Do I need to wear a mask?"
license: mit
language: en
---
# Multi2ConvAI-Corona: finetuned Bert for English
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Corona (more details about our us... |
1,094 | inovex/multi2convai-corona-fr-bert | [
"corona.traffic",
"corona.supplies",
"corona.quarantine",
"corona.masks",
"corona.illness",
"corona.package",
"corona.vaccine",
"corona.rumors",
"corona.risk",
"corona.course",
"corona.symptoms",
"corona.patients",
"corona.deathRate",
"corona.infect",
"corona.protect",
"corona.definiti... | ---
tags:
- text-classification
widget:
- text: "Dois-je porter un masque?"
license: mit
language: fr
---
# Multi2ConvAI-Corona: finetuned Bert for French
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Corona (more details about our use cases: ([en](https://multi2conv.ai/en/... |
1,095 | inovex/multi2convai-corona-it-bert | [
"corona.traffic",
"corona.supplies",
"corona.quarantine",
"corona.masks",
"corona.illness",
"corona.package",
"corona.vaccine",
"corona.rumors",
"corona.risk",
"corona.course",
"corona.symptoms",
"corona.patients",
"corona.deathRate",
"corona.infect",
"corona.protect",
"corona.definiti... | ---
tags:
- text-classification
widget:
- text: "Devo indossare una maschera?"
license: mit
language: it
---
# Multi2ConvAI-Corona: finetuned Bert for Italian
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Corona (more details about our use cases: ([en](https://m... |
1,096 | inovex/multi2convai-logistics-de-bert | [
"details.address",
"tour.postcode.select",
"tour.finish",
"details.safeplace",
"details.preferedNeighbour",
"details.avoidNeighbour",
"tour.job.collected",
"no",
"yes",
"tour.start",
"tour.details",
"tour.job.signature",
"tour.job.delivered",
"select",
"tour.job.safePlace",
"safeplace"... | ---
tags:
- text-classification
widget:
- text: "Wo kann ich das Paket ablegen?"
license: mit
language: de
---
# Multi2ConvAI-Logistics: finetuned Bert for German
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Logistics (more details about our use cases: ([en](ht... |
1,097 | inovex/multi2convai-logistics-en-bert | [
"details.address",
"tour.postcode.select",
"tour.finish",
"details.safeplace",
"details.preferedNeighbour",
"details.avoidNeighbour",
"tour.job.collected",
"no",
"yes",
"tour.start",
"tour.details",
"tour.job.signature",
"tour.job.delivered",
"select",
"tour.job.safePlace",
"safeplace"... | ---
tags:
- text-classification
widget:
- text: "Where can I put the parcel?"
license: mit
language: en
---
# Multi2ConvAI-Logistics: finetuned Bert for English
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Logistics (more details about our use cases: ([en](http... |
1,098 | inovex/multi2convai-logistics-hr-bert | [
"details.address",
"tour.postcode.select",
"tour.finish",
"details.safeplace",
"details.preferedNeighbour",
"details.avoidNeighbour",
"tour.job.collected",
"no",
"yes",
"tour.start",
"tour.details",
"tour.job.signature",
"tour.job.delivered",
"select",
"tour.job.safePlace",
"safeplace"... | ---
tags:
- text-classification
widget:
- text: "gdje mogu staviti paket?"
license: mit
language: hr
---
# Multi2ConvAI-Logistics: finetuned Bert for Croatian
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Logistics (more details about our use cases: ([en](https:... |
1,099 | inovex/multi2convai-logistics-pl-bert | [
"details.address",
"tour.postcode.select",
"tour.finish",
"details.safeplace",
"details.preferedNeighbour",
"details.avoidNeighbour",
"tour.job.collected",
"no",
"yes",
"tour.start",
"tour.details",
"tour.job.signature",
"tour.job.delivered",
"select",
"tour.job.safePlace",
"safeplace"... | ---
tags:
- text-classification
widget:
- text: "gdzie mogę umieścić paczkę?"
license: mit
language: pl
---
# Multi2ConvAI-Logistics: finetuned Bert for Polish
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Logistics (more details about our use cases: ([en](https... |
1,100 | inovex/multi2convai-logistics-tr-bert | [
"details.address",
"tour.postcode.select",
"tour.finish",
"details.safeplace",
"details.preferedNeighbour",
"details.avoidNeighbour",
"tour.job.collected",
"no",
"yes",
"tour.start",
"tour.details",
"tour.job.signature",
"tour.job.delivered",
"select",
"tour.job.safePlace",
"safeplace"... | ---
tags:
- text-classification
widget:
- text: "paketi nereye koyabilirim?"
license: mit
language: tr
---
# Multi2ConvAI-Logistics: finetuned Bert for Turkish
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Logistics (more details about our use cases: ([en](https... |
1,101 | inovex/multi2convai-quality-de-bert | [
"neo.magnetklammern",
"neo.start",
"neo.back",
"neo.gearbox",
"neo.motor.brushcollar",
"neo.motor.worm",
"neo.magnet",
"neo.magnetisierung",
"neo.motor",
"neo.verschaubung",
"neo.zusammenfuehrung",
"neo.zahnradgross",
"neo.zahnradklein",
"neo.yes",
"neo.no",
"neo.einpressen",
"neo.mo... | ---
tags:
- text-classification
widget:
- text: "Starte das Programm"
license: mit
language: de
---
# Multi2ConvAI-Quality: finetuned Bert for German
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Quality (more details about our use cases: ([en](https://multi2con... |
1,102 | inovex/multi2convai-quality-de-mbert | [
"neo.magnetklammern",
"neo.start",
"neo.back",
"neo.gearbox",
"neo.motor.brushcollar",
"neo.motor.worm",
"neo.magnet",
"neo.magnetisierung",
"neo.motor",
"neo.verschaubung",
"neo.zusammenfuehrung",
"neo.zahnradgross",
"neo.zahnradklein",
"neo.yes",
"neo.no",
"neo.einpressen",
"neo.mo... | ---
tags:
- text-classification
widget:
- text: "Starte das Programm"
license: mit
language: de
---
# Multi2ConvAI-Quality: finetuned MBert for German
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Quality (more details about our use cases: ([en](https://multi2co... |
1,103 | inovex/multi2convai-quality-en-bert | [
"neo.magnetklammern",
"neo.start",
"neo.back",
"neo.gearbox",
"neo.motor.brushcollar",
"neo.motor.worm",
"neo.magnet",
"neo.magnetisierung",
"neo.motor",
"neo.verschaubung",
"neo.zusammenfuehrung",
"neo.zahnradgross",
"neo.zahnradklein",
"neo.yes",
"neo.no",
"neo.einpressen",
"neo.mo... | ---
tags:
- text-classification
widget:
- text: "Start the program"
license: mit
language: en
---
# Multi2ConvAI-Quality: finetuned Bert for English
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Quality (more details about our use cases: ([en](https://multi2conv... |
1,104 | inovex/multi2convai-quality-en-mbert | [
"neo.magnetklammern",
"neo.start",
"neo.back",
"neo.gearbox",
"neo.motor.brushcollar",
"neo.motor.worm",
"neo.magnet",
"neo.magnetisierung",
"neo.motor",
"neo.verschaubung",
"neo.zusammenfuehrung",
"neo.zahnradgross",
"neo.zahnradklein",
"neo.yes",
"neo.no",
"neo.einpressen",
"neo.mo... | ---
tags:
- text-classification
widget:
- text: "Start the program"
license: mit
language: en
---
# Multi2ConvAI-Quality: finetuned MBert for English
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Quality (more details about our use cases: ([en](https://multi2con... |
1,105 | inovex/multi2convai-quality-fr-bert | [
"neo.magnetklammern",
"neo.start",
"neo.back",
"neo.gearbox",
"neo.motor.brushcollar",
"neo.motor.worm",
"neo.magnet",
"neo.magnetisierung",
"neo.motor",
"neo.verschaubung",
"neo.zusammenfuehrung",
"neo.zahnradgross",
"neo.zahnradklein",
"neo.yes",
"neo.no",
"neo.einpressen",
"neo.mo... | ---
tags:
- text-classification
widget:
- text: "Lancer le programme"
license: mit
language: fr
---
# Multi2ConvAI-Quality: finetuned Bert for French
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Quality (more details about our use cases: ([en](https://multi2con... |
1,106 | inovex/multi2convai-quality-fr-mbert | [
"neo.magnetklammern",
"neo.start",
"neo.back",
"neo.gearbox",
"neo.motor.brushcollar",
"neo.motor.worm",
"neo.magnet",
"neo.magnetisierung",
"neo.motor",
"neo.verschaubung",
"neo.zusammenfuehrung",
"neo.zahnradgross",
"neo.zahnradklein",
"neo.yes",
"neo.no",
"neo.einpressen",
"neo.mo... | ---
tags:
- text-classification
widget:
- text: "Lancer le programme"
license: mit
language: fr
---
# Multi2ConvAI-Quality: finetuned MBert for French
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Quality (more details about our use cases: ([en](https://multi2co... |
1,107 | inovex/multi2convai-quality-it-bert | [
"neo.magnetklammern",
"neo.start",
"neo.back",
"neo.gearbox",
"neo.motor.brushcollar",
"neo.motor.worm",
"neo.magnet",
"neo.magnetisierung",
"neo.motor",
"neo.verschaubung",
"neo.zusammenfuehrung",
"neo.zahnradgross",
"neo.zahnradklein",
"neo.yes",
"neo.no",
"neo.einpressen",
"neo.mo... | ---
tags:
- text-classification
widget:
- text: "Avviare il programma"
license: mit
language: it
---
# Multi2ConvAI-Quality: finetuned Bert for Italian
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Quality (more details about our use cases: ([en](https://multi2c... |
1,108 | inovex/multi2convai-quality-it-mbert | [
"neo.magnetklammern",
"neo.start",
"neo.back",
"neo.gearbox",
"neo.motor.brushcollar",
"neo.motor.worm",
"neo.magnet",
"neo.magnetisierung",
"neo.motor",
"neo.verschaubung",
"neo.zusammenfuehrung",
"neo.zahnradgross",
"neo.zahnradklein",
"neo.yes",
"neo.no",
"neo.einpressen",
"neo.mo... | ---
tags:
- text-classification
widget:
- text: "Avviare il programma"
license: mit
language: it
---
# Multi2ConvAI-Quality: finetuned MBert for Italian
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Quality (more details about our use cases: ([en](https://multi2... |
1,109 | ipuneetrathore/bert-base-cased-finetuned-finBERT | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | ## FinBERT
Code for importing and using this model is available [here](https://github.com/ipuneetrathore/BERT_models)
|
1,110 | ishan/bert-base-uncased-mnli | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | ---
language: en
thumbnail:
tags:
- pytorch
- text-classification
datasets:
- MNLI
---
# bert-base-uncased finetuned on MNLI
## Model Details and Training Data
We used the pretrained model from [bert-base-uncased](https://huggingface.co/bert-base-uncased) and finetuned it on [MultiNLI](https://cims.nyu.edu/~sbowman... |
1,111 | ishan/distilbert-base-uncased-mnli | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | ---
language: en
thumbnail:
tags:
- pytorch
- text-classification
datasets:
- MNLI
---
# distilbert-base-uncased finetuned on MNLI
## Model Details and Training Data
We used the pretrained model from [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) and finetuned it on [MultiNLI](https://cim... |
1,112 | ismaelardo/BETO_3d | [
"LABEL_0",
"LABEL_1",
"LABEL_10",
"LABEL_11",
"LABEL_12",
"LABEL_13",
"LABEL_14",
"LABEL_15",
"LABEL_16",
"LABEL_17",
"LABEL_18",
"LABEL_19",
"LABEL_2",
"LABEL_20",
"LABEL_21",
"LABEL_22",
"LABEL_23",
"LABEL_24",
"LABEL_25",
"LABEL_26",
"LABEL_27",
"LABEL_28",
"LABEL_29",... | Este es el primer modelo de prueba BETO_3D |
1,113 | ivanlau/language-detection-fine-tuned-on-xlm-roberta-base | [
"Arabic",
"Basque",
"Breton",
"Catalan",
"Chinese_China",
"Chinese_Hongkong",
"Chinese_Taiwan",
"Chuvash",
"Czech",
"Dhivehi",
"Dutch",
"English",
"Esperanto",
"Estonian",
"French",
"Frisian",
"Georgian",
"German",
"Greek",
"Hakha_Chin",
"Indonesian",
"Interlingua",
"Ital... | ---
license: mit
tags:
- generated_from_trainer
datasets:
- common_language
metrics:
- accuracy
model-index:
- name: language-detection-fine-tuned-on-xlm-roberta-base
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: common_language
type: common_language... |
1,114 | j-hartmann/emotion-english-distilroberta-base | [
"anger",
"disgust",
"fear",
"joy",
"neutral",
"sadness",
"surprise"
] | ---
language: "en"
tags:
- distilroberta
- sentiment
- emotion
- twitter
- reddit
widget:
- text: "Oh wow. I didn't know that."
- text: "This movie always makes me cry.."
- text: "Oh Happy Day"
---
# Emotion English DistilRoBERTa-base
# Description ℹ
With this model, you can classify emotions in English text data.... |
1,115 | j-hartmann/emotion-english-roberta-large | [
"anger",
"disgust",
"fear",
"joy",
"neutral",
"sadness",
"surprise"
] | ---
language: "en"
tags:
- roberta
- sentiment
- emotion
- twitter
- reddit
widget:
- text: "Oh wow. I didn't know that."
- text: "This movie always makes me cry.."
- text: "Oh Happy Day"
---
## Description ℹ
With this model, you can classify emotions in English text data. The model was trained on 6 diverse datase... |
1,116 | j-hartmann/mind-perception-roberta-base | [
"low",
"high"
] | ---
language: "en"
tags:
- roberta
widget:
- text: "Alexa is part of our family. She is simply amazing!"
- text: "I use my smart assistant for may things. It's incredibly useful."
---
This RoBERTa-based model ("MindMiner") can classify the degree of mind perception in English language text in 2 classes:
- high mind... |
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