modelId stringlengths 6 107 | label list | readme stringlengths 0 56.2k | readme_len int64 0 56.2k |
|---|---|---|---|
boychaboy/MNLI_distilbert-base-cased | [
"contradiction",
"entailment",
"neutral"
] | Entry not found | 15 |
cardiffnlp/bertweet-base-stance-atheism | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | 0 | |
JacopoBandoni/BioBertRelationGenesDiseases | null | ---
license: afl-3.0
widget:
- text: "The case of a 72-year-old male with @DISEASE$ with poor insulin control (fasting hyperglycemia greater than 180 mg/dl) who had a long-standing polyuric syndrome is here presented. Hypernatremia and plasma osmolality elevated together with a low urinary osmolality led to the suspici... | 1,147 |
Sreevishnu/funnel-transformer-small-imdb | [
"neg",
"pos"
] | ---
license: apache-2.0
language: en
widget:
- text: "In the garden of wonderment that is the body of work by the animation master Hayao Miyazaki, his 2001 gem 'Spirited Away' is at once one of his most accessible films to a Western audience and the one most distinctly rooted in Japanese culture and lore. The tale of C... | 4,520 |
dinalzein/xlm-roberta-base-finetuned-language-identification | [
"ar",
"bg",
"de",
"el",
"en",
"es",
"fr",
"hi",
"it",
"ja",
"nl",
"pl",
"pt",
"ru",
"sw",
"th",
"tr",
"ur",
"vi",
"zh"
] | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: xlm-roberta-base-finetuned-language-identification
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, the... | 2,234 |
cwkeam/m-ctc-t-large-sequence-lid | [
"ab",
"ar",
"as",
"br",
"ca",
"cnh",
"cs",
"cv",
"cy",
"de",
"dv",
"el",
"en",
"eo",
"es",
"et",
"eu",
"fa",
"fi",
"fr",
"fy-NL",
"ga-IE",
"hi",
"hsb",
"hu",
"ia",
"id",
"it",
"ja",
"ka",
"kab",
"ky",
"lg",
"lt",
"lv",
"mn",
"mt",
"nl",
"or... | ---
language: en
datasets:
- librispeech_asr
- common_voice
tags:
- speech
license: apache-2.0
---
# M-CTC-T
Massively multilingual speech recognizer from Meta AI. The model is a 1B-param transformer encoder, with a CTC head over 8065 character labels and a language identification head over 60 language ID labels. I... | 2,741 |
p-christ/QandAClassifier | [
"ACCEPTED",
"REJECTED"
] | Entry not found | 15 |
IMSyPP/hate_speech_nl | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3"
] | ---
language:
- nl
license: mit
---
# Hate Speech Classifier for Social Media Content in Dutch
A monolingual model for hate speech classification of social media content in Dutch. The model was trained on 20000 social media posts (youtube, twitter, facebook) and tested on an independent test set of 2000 posts. It ... | 716 |
NbAiLab/nb-bert-base-samisk | null | ---
license: apache-2.0
---
| 31 |
TehranNLP-org/bert-base-uncased-cls-hatexplain | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | Entry not found | 15 |
classla/sloberta-frenk-hate | null | ---
language: "sl"
tags:
- text-classification
- hate-speech
widget:
- text: "Silva, ti si grda in neprijazna"
---
Text classification model based on `EMBEDDIA/sloberta` and fine-tuned on the [FRENK dataset](https://www.clarin.si/repository/xmlui/handle/11356/1433) comprising of LGBT and migrant hatespeech. Only the... | 3,464 |
lewtun/minilm-finetuned-emotion | [
"anger",
"fear",
"joy",
"love",
"sadness",
"surprise"
] | ---
license: mit
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- f1
model-index:
- name: minilm-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: default
metrics:
- name: F1
... | 1,862 |
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... | 1,002 |
navteca/nli-deberta-v3-large | [
"contradiction",
"entailment",
"neutral"
] | ---
datasets:
- multi_nli
- snli
language: en
license: apache-2.0
metrics:
- accuracy
pipeline_tag: zero-shot-classification
tags:
- microsoft/deberta-v3-large
---
# Cross-Encoder for Natural Language Inference
This model was trained using [SentenceTransformers](https://sbert.net) [Cross-Encoder](https://www.sbert.ne... | 2,781 |
tdrenis/finetuned-bot-detector | null | Student project that fine-tuned the roberta-base-openai-detector model on the Twibot-20 dataset. | 96 |
ChrisLiewJY/BERTweet-Hedge | null | ---
license: mit
language:
- en
tags:
- uncertainty-detection
- social-media
- text-classification
widget:
- text: "It seems like Bitcoin prices are heading into bearish territory."
example_title: "Hedge Detection (Positive - Label 1)"
- text: "Bitcoin prices have fallen by 42% in the last 30 days."
example_titl... | 1,041 |
SetFit/distilbert-base-uncased__enron_spam__all-train | [
"ham",
"spam"
] | Entry not found | 15 |
Tatyana/rubert_conversational_cased_sentiment | null | ---
language:
- ru
tags:
- sentiment
- text-classification
datasets:
- Tatyana/ru_sentiment_dataset
---
# Keras model with ruBERT conversational embedder for Sentiment Analysis
Russian texts sentiment classification.
Model trained on [Tatyana/ru_sentiment_dataset](https://huggingface.co/datasets/Tatyana/ru_sentiment_... | 860 |
boychaboy/SNLI_roberta-large | [
"contradiction",
"entailment",
"neutral"
] | Entry not found | 15 |
fergusq/finbert-finnsentiment | [
"NEGATIVE",
"NEUTRAL",
"POSITIVE"
] | ---
language: fi
---
# 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).
| 182 |
wanyu/IteraTeR-ROBERTA-Intention-Classifier | [
"clarity",
"coherence",
"fluency",
"meaning-changed",
"style"
] | ---
datasets:
- IteraTeR_full_sent
---
# IteraTeR RoBERTa model
This model was obtained by fine-tuning [roberta-large](https://huggingface.co/roberta-large) on [IteraTeR-human-sent](https://huggingface.co/datasets/wanyu/IteraTeR_human_sent) dataset.
Paper: [Understanding Iterative Revision from Human-Written Text](ht... | 2,927 |
UT/BMW | null | Entry not found | 15 |
jonas/sdg_classifier_osdg | [
"1",
"10",
"11",
"12",
"13",
"14",
"15",
"2",
"3",
"4",
"5",
"6",
"7",
"8",
"9"
] | ---
language: en
widget:
- text: "Ending all forms of discrimination against women and girls is not only a basic human right, but it also crucial to accelerating sustainable development. It has been proven time and again, that empowering women and girls has a multiplier effect, and helps drive up economic growth and de... | 2,365 |
tezign/Erlangshen-Sentiment-FineTune | null | ---
language: zh
tags:
- sentiment-analysis
- pytorch
widget:
- text: "房间非常非常小，内窗，特别不透气，因为夜里走廊灯光是亮的，内窗对着走廊，窗帘又不能完全拉死，怎么都会有一道光射进来。"
- text: "尽快有洗衣房就好了。"
- text: "很好，干净整洁，交通方便。"
- text: "干净整洁很好"
---
# Note
BERT based sentiment analysis, finetune based on https://huggingface.co/IDEA-CCNL/Erlangshen-Roberta-330M-Sentimen... | 1,988 |
ReynaQuita/twitter_disaster_bert_large | null | Entry not found | 15 |
abhishek/autonlp-japanese-sentiment-59362 | [
"negative",
"positive"
] | ---
tags: autonlp
language: ja
widget:
- text: "I love AutoNLP 🤗"
datasets:
- abhishek/autonlp-data-japanese-sentiment
---
# Model Trained Using AutoNLP
- Problem type: Binary Classification
- Model ID: 59362
## Validation Metrics
- Loss: 0.13092292845249176
- Accuracy: 0.9527127414314258
- Precision: 0.9634070704... | 1,096 |
finiteautomata/bert-contextualized-hate-speech-es | [
"Hateful",
"Not hateful"
] | Entry not found | 15 |
google/tapas-large-finetuned-tabfact | null | ---
language: en
tags:
- tapas
- sequence-classification
license: apache-2.0
datasets:
- tab_fact
---
# TAPAS large model fine-tuned on Tabular Fact Checking (TabFact)
This model has 2 versions which can be used. The latest version, which is the default one, corresponds to the `tapas_tabfact_inter_masklm_large_rese... | 4,870 |
nateraw/codecarbon-text-classification | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
model-index:
- name: codecarbon-text-classification
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 com... | 1,067 |
ykacer/bert-base-cased-imdb-sequence-classification | null |
---
language:
- en
thumbnail: https://raw.githubusercontent.com/JetRunner/BERT-of-Theseus/master/bert-of-theseus.png
tags:
- sequence
- classification
license: apache-2.0
datasets:
- imdb
metrics:
- accuracy
---
| 213 |
rasta/distilbert-base-uncased-finetuned-fashion | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-fashion
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, t... | 1,394 |
tinkoff-ai/response-quality-classifier-base | [
"relevance",
"specificity"
] | ---
license: mit
widget:
- text: "[CLS]привет[SEP]привет![SEP]как дела?[RESPONSE_TOKEN]супер, вот только проснулся, у тебя как?"
example_title: "Dialog example 1"
- text: "[CLS]привет[SEP]привет![SEP]как дела?[RESPONSE_TOKEN]норм"
example_title: "Dialog example 2"
- text: "[CLS]привет[SEP]привет![SEP]как дела?[RESP... | 2,593 |
PrimeQA/tydiqa-boolean-answer-classifier | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | ---
license: apache-2.0
---
## Model description
An answer classification model for boolean questions based on XLM-RoBERTa.
The answer classifier takes as input a boolean question and a passage, and returns a label (yes, no-answer, no).
The model was initialized with [xlm-roberta-large](https://huggingface.co/xlm... | 1,770 |
Tomas23/twitter-roberta-base-mar2022-finetuned-sentiment | [
"negative",
"neutral",
"positive"
] | Entry not found | 15 |
okho0653/Bio_ClinicalBERT-zero-shot-tokenizer-truncation-sentiment-model | null | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: Bio_ClinicalBERT-zero-shot-tokenizer-truncation-sentiment-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... | 1,118 |
adamnik/electra-event-detection | null | ---
license: mit
---
| 21 |
Cameron/BERT-mdgender-convai-binary | null | Entry not found | 15 |
LilaBoualili/bert-sim-pair | null | At its core it uses an BERT-Base model (bert-base-uncased) fine-tuned on the MS MARCO passage classification task using the Sim-Pair marking strategy that highlights exact term matches between the query and the passage via marker tokens (#). It can be loaded using the TF/AutoModelForSequenceClassification classes.
Ref... | 441 |
SetFit/distilbert-base-uncased__sst5__all-train | [
"negative",
"neutral",
"positive",
"very negative",
"very positive"
] | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased__sst5__all-train
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then re... | 1,613 |
Narsil/bart-large-mnli-opti | [
"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... | 3,793 |
anahitapld/dbd_bert_da_simple | [
"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",... | ---
license: apache-2.0
---
| 28 |
StanfordAIMI/covid-radbert | [
"no COVID-19",
"uncertain COVID-19",
"COVID-19"
] | ---
widget:
- text: "procedure: single ap view of the chest comparison: none findings: no surgical hardware nor tubes. lungs, pleura: low lung volumes, bilateral airspace opacities. no pneumothorax or pleural effusion. cardiovascular and mediastinum: the cardiomediastinal silhouette seems stable. impression: 1. patchy ... | 1,299 |
airKlizz/xlm-roberta-base-germeval21-toxic-with-data-augmentation | null | Entry not found | 15 |
aubmindlab/aragpt2-mega-detector-long | [
"human-written",
"machine-generated"
] | ---
language: ar
widget:
- text: "وإذا كان هناك من لا يزال يعتقد أن لبنان هو سويسرا الشرق ، فهو مخطئ إلى حد بعيد . فلبنان ليس سويسرا ، ولا يمكن أن يكون كذلك . لقد عاش اللبنانيون في هذا البلد منذ ما يزيد عن ألف وخمسمئة عام ، أي منذ تأسيس الإمارة الشهابية التي أسسها الأمير فخر الدين المعني الثاني ( 1697 - 1742 )"
---
... | 1,749 |
cardiffnlp/bertweet-base-stance-climate | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | 0 | |
mrm8488/flaubert-small-finetuned-movie-review-sentiment-analysis | null | Entry not found | 15 |
unicamp-dl/mMiniLM-L6-v2-mmarco-v1 | [
"LABEL_0"
] | ---
language: pt
license: mit
tags:
- msmarco
- miniLM
- pytorch
- tensorflow
- pt
- pt-br
datasets:
- msmarco
widget:
- text: "Texto de exemplo em português"
inference: false
---
# mMiniLM-L6-v2 Reranker finetuned on mMARCO
## Introduction
mMiniLM-L6-v2-mmarco-v1 is a multilingual miniLM-based model finetuned on a mul... | 1,545 |
HiTZ/A2T_RoBERTa_SMFA_WikiEvents-arg_ACE-arg | [
"contradiction",
"entailment",
"neutral"
] | ---
pipeline_tag: zero-shot-classification
datasets:
- snli
- anli
- multi_nli
- multi_nli_mismatch
- fever
---
# A2T Entailment model
**Important:** These pretrained entailment models are intended to be used with the [Ask2Transformers](https://github.com/osainz59/Ask2Transformers) library but are also fully compatib... | 3,612 |
aomar85/fine-tuned-arabert-random-negative | null | ---
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: fine-tuned-arabert-random-negative
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then re... | 1,864 |
sschellhammer/SciTweets_SciBert | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | ---
license: cc-by-4.0
widget:
- text: "Study: Shifts in electricity generation spur net job growth, but coal jobs decline - via @DukeU https://www.eurekalert.org/news-releases/637217"
example_title: "All categories"
- text: "Shifts in electricity generation spur net job growth, but coal jobs decline"
example_title... | 896 |
Theivaprakasham/sentence-transformers-paraphrase-MiniLM-L6-v2-twitter_sentiment | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | Entry not found | 15 |
TransQuest/monotransquest-da-any_en | [
"LABEL_0"
] | ---
language: multilingual-en
tags:
- Quality Estimation
- monotransquest
- DA
license: apache-2.0
---
# TransQuest: Translation Quality Estimation with Cross-lingual Transformers
The goal of quality estimation (QE) is to evaluate the quality of a translation without having access to a reference translation. High-acc... | 5,407 |
airKlizz/gbert-base-germeval21-toxic | null | Entry not found | 15 |
arianpasquali/twitter-xlm-roberta-base-sentiment-finetunned | [
"Negative",
"Neutral",
"Positive"
] | Entry not found | 15 |
blizrys/biobert-v1.1-finetuned-pubmedqa | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | ---
tags:
- generated_from_trainer
datasets:
- null
metrics:
- accuracy
model-index:
- name: biobert-v1.1-finetuned-pubmedqa
results:
- task:
name: Text Classification
type: text-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.7
---
<!-- This model card has been gen... | 2,056 |
cardiffnlp/twitter-roberta-base-stance-hillary | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | 0 | |
mariagrandury/roberta-base-finetuned-sms-spam-detection | null | ---
license: mit
tags:
- generated_from_trainer
datasets:
- sms_spam
metrics:
- accuracy
model-index:
- name: roberta-base-finetuned-sms-spam-detection
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: sms_spam
type: sms_spam
args: plain_text
m... | 1,667 |
persiannlp/parsbert-base-parsinlu-entailment | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | ---
language:
- fa
- multilingual
thumbnail: https://upload.wikimedia.org/wikipedia/commons/a/a2/Farsi.svg
tags:
- entailment
- parsbert
- persian
- farsi
license: cc-by-nc-sa-4.0
datasets:
- parsinlu
metrics:
- accuracy
---
# Textual Entailment (مدل برای پاسخ به استلزام منطقی)
This is a model for textual entailment ... | 1,639 |
spencerh/rightpartisan | null | # Text classifier using DistilBERT to determine Partisanship
## This is one of the single-class partisan detecting models. (see leftpartisan/leftcenterpartisan/rightcenterpartisan/centerpartisan)
label_0 refers to "other" while label_1 refers to "right" (right as in right-leaning).
This was trained with 40,000 arti... | 460 |
searle-j/kote_for_easygoing_people | [
"감동/감탄",
"경악",
"고마움",
"공포/무서움",
"귀찮음",
"기대감",
"기쁨",
"깨달음",
"놀람",
"당황/난처",
"부끄러움",
"부담/안_내킴",
"불쌍함/연민",
"불안/걱정",
"불평/불만",
"비장함",
"뿌듯함",
"서러움",
"슬픔",
"신기함/관심",
"아껴주는",
"안심/신뢰",
"안타까움/실망",
"어이없음",
"없음",
"역겨움/징그러움",
"우쭐댐/무시함",
"의심/불신",
"재미없음",
"절망",
"존경",
"죄... | ---
license: mit
---
| 21 |
Abdelrahman-Rezk/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... | 4,165 |
CEBaB/lstm.CEBaB.sa.2-class.exclusive.seed_42 | [
"0",
"1"
] | Entry not found | 15 |
Rhuax/MiniLMv2-L12-H384-distilled-finetuned-spam-detection | [
"ham",
"spam"
] | ---
tags:
- generated_from_trainer
datasets:
- sms_spam
metrics:
- accuracy
model-index:
- name: MiniLMv2-L12-H384-distilled-finetuned-spam-detection
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: sms_spam
type: sms_spam
args: plain_text
met... | 2,064 |
mgonnav/finetuning-pysentimiento-war-tweets | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4"
] | ---
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: finetuning-pysentimiento-war-tweets
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. -... | 1,607 |
postpandas/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... | 1,807 |
BritishLibraryLabs/bl-books-genre | null | ---
language: multilingual
tags:
- genre
- books
- library
- historic
- glam
license: mit
metrics:
- f1
widget:
- text: "Poems on various subjects. Whereto is prefixed a short essay on the structure of English verse"
- text: "Two Centuries of Soho: its institutions, firms, and amusements. By the Clergy of St. Anne's, S... | 7,905 |
albertvillanova/autonlp-indic_glue-multi_class_classification-1e67664-1311135 | [
"0",
"1",
"2",
"3",
"4",
"5"
] | ---
tags: autonlp
language: bn
widget:
- text: "I love AutoNLP 🤗"
datasets:
- albertvillanova/autonlp-data-indic_glue-multi_class_classification-1e67664
---
# Model Trained Using AutoNLP
- Problem type: Multi-class Classification
- Model ID: 1311135
## Validation Metrics
- Loss: 0.35616958141326904
- Accuracy: 0.8... | 1,455 |
hyunwoongko/jaberta-base-ja-xnli | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | Entry not found | 15 |
batterydata/batteryscibert-uncased-abstract | [
"battery",
"non-battery"
] | ---
language: en
tags: Text Classification
license: apache-2.0
datasets:
- batterydata/paper-abstracts
metrics: glue
---
# BatterySciBERT-uncased for Battery Abstract Classification
**Language model:** batteryscibert-uncased
**Language:** English
**Downstream-task:** Text Classification
**Training dat... | 1,474 |
ibm/roberta-large-vira-intents | [
"LABEL_0",
"LABEL_1",
"LABEL_10",
"LABEL_100",
"LABEL_101",
"LABEL_102",
"LABEL_103",
"LABEL_104",
"LABEL_105",
"LABEL_106",
"LABEL_107",
"LABEL_108",
"LABEL_109",
"LABEL_11",
"LABEL_110",
"LABEL_111",
"LABEL_112",
"LABEL_113",
"LABEL_114",
"LABEL_115",
"LABEL_116",
"LABEL_... | ---
language:
- en
tags:
- intent detection
license: "other"
datasets:
- ibm/vira-intents
metrics:
- accuracy
widget:
- text: "Should I be concerned about side effects of the vaccine if I'm breastfeeding?} & Is breastfeeding safe with the vaccine"
example_title: "Breastfeeding"
- text: "Does the vaccine prevent trans... | 1,693 |
RJuro/Da-HyggeBERT | [
"afsky",
"begær",
"beundring",
"forlegenhed",
"fornøjelse",
"fortrydelse",
"forvirring",
"frygt",
"glæde",
"indsigt",
"irritation",
"kærlighed",
"lettelse",
"medhold",
"misbilligelse",
"nervøsitet",
"neutral",
"nysgerrighed",
"omsorg",
"optimisme",
"overraskelse",
"skuffels... | ---
language: da
tags:
- danish
- bert
- sentiment
- text-classification
- Maltehb/danish-bert-botxo
- Helsinki-NLP/opus-mt-en-da
- go-emotion
- Certainly
license: cc-by-4.0
datasets:
- go_emotions
metrics:
- Accuracy
widget:
- text: "Det er så sødt af dig at tænke på andre på den måde ved du det?"
- text: "Jeg vil ger... | 2,086 |
Team-PIXEL/pixel-base-finetuned-sst2 | [
"negative",
"positive"
] | ---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
model-index:
- name: pixel-base-finetuned-sst2
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. -->
... | 1,188 |
CAMeL-Lab/bert-base-arabic-camelbert-ca-sentiment | [
"negative",
"neutral",
"positive"
] | ---
language:
- ar
license: apache-2.0
widget:
- text: "أنا بخير"
---
# CAMeLBERT-CA SA Model
## Model description
**CAMeLBERT-CA SA Model** is a Sentiment Analysis (SA) model that was built by fine-tuning the [CAMeLBERT Classical Arabic (CA)](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-ca/) model.
Fo... | 3,364 |
Cameron/BERT-SBIC-offensive | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | Entry not found | 15 |
Connor-tech/bert_cn_finetuning | [
"LABEL_0",
"LABEL_1"
] | Entry not found | 15 |
Maelstrom77/roberta-large-mnli | [
"CONTRADICTION",
"ENTAILMENT",
"NEUTRAL"
] | Entry not found | 15 |
RecordedFuture/Swedish-Sentiment-Fear | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | ---
language: sv
license: mit
---
## Swedish BERT models for sentiment analysis
[Recorded Future](https://www.recordedfuture.com/) together with [AI Sweden](https://www.ai.se/en) releases two language models for sentiment analysis in Swedish. The two models are based on the [KB\/bert-base-swedish-cased](https://huggi... | 3,299 |
blizrys/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-finetuned-pubmedqa | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | ---
license: mit
tags:
- generated_from_trainer
datasets:
- null
metrics:
- accuracy
model-index:
- name: BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-finetuned-pubmedqa
results:
- task:
name: Text Classification
type: text-classification
metrics:
- name: Accuracy
type: accuracy
... | 2,229 |
boychaboy/MNLI_albert-base-v2 | [
"contradiction",
"entailment",
"neutral"
] | Entry not found | 15 |
cardiffnlp/bertweet-base-stance-hillary | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | 0 | |
lighteternal/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-finetuned-mnli | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | ---
language: en
tags:
- textual-entailment
- nli
- pytorch
datasets:
- mnli
license: mit
widget :
- text: "EpCAM is overexpressed in breast cancer. </s></s> EpCAM is downregulated in breast cancer."
---
# BiomedNLP-PubMedBERT finetuned on textual entailment (NLI)
The [microsoft/BiomedNLP-PubMedBERT-base-uncased-abst... | 2,251 |
patrickvonplaten/deberta_v3_amazon_reviews | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3",
"LABEL_4"
] | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: deberta_v3_amazon_reviews
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. -->
# deberta_v3_amazo... | 1,097 |
Hate-speech-CNERG/english-abusive-MuRIL | null | ---
language: en
license: afl-3.0
---
This model is used detecting **abusive speech** in **English**. It is finetuned on MuRIL model using English abusive speech dataset.
The model is trained with learning rates of 2e-5. Training code can be found at this [url](https://github.com/hate-alert/IndicAbusive)
LABEL_0 :-> ... | 960 |
Cristian-dcg/beto-sentiment-analysis-finetuned-onpremise | [
"NEG",
"NEU",
"POS"
] | ---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: beto-sentiment-analysis-finetuned-onpremise
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... | 1,525 |
Clody0071/distilbert-base-multilingual-cased-finetuned-similarite | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- pawsx
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-multilingual-cased-finetuned-similarite
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: pawsx
type: pawsx
args:... | 1,843 |
binay1999/text_classification_cybertexts | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: text_classification_cybertexts
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. -->
# text... | 1,431 |
Maha/xlmtwtroberta_label2 | null | Entry not found | 15 |
CAMeL-Lab/bert-base-arabic-camelbert-da-poetry | [
"البسيط",
"الخفيف",
"الدوبيت",
"الرجز",
"الرمل",
"السريع",
"السلسلة",
"الطويل",
"الكامل",
"المتدارك",
"المتقارب",
"المجتث",
"المديد",
"المضارع",
"المقتضب",
"المنسرح",
"المواليا",
"الهزج",
"الوافر",
"شعر التفعيلة",
"شعر حر",
"عامي",
"موشح"
] | ---
language:
- ar
license: apache-2.0
widget:
- text: 'الخيل والليل والبيداء تعرفني [SEP] والسيف والرمح والقرطاس والقلم'
---
# CAMeLBERT-DA Poetry Classification Model
## Model description
**CAMeLBERT-DA Poetry Classification Model** is a poetry classification model that was built by fine-tuning the [CAMeLBERT Diale... | 3,383 |
CAMeL-Lab/bert-base-arabic-camelbert-mix-did-madar-corpus6 | [
"BEI",
"CAI",
"DOH",
"MSA",
"RAB",
"TUN"
] | ---
language:
- ar
license: apache-2.0
widget:
- text: "عامل ايه ؟"
---
# CAMeLBERT-Mix DID MADAR Corpus6 Model
## Model description
**CAMeLBERT-Mix DID MADAR Corpus6 Model** is a dialect identification (DID) model that was built by fine-tuning the [CAMeLBERT-Mix](https://huggingface.co/CAMeL-Lab/bert-base-arabic-cam... | 2,938 |
DTAI-KULeuven/mbert-corona-tweets-belgium-curfew-support | [
"not-applicable\n",
"ok\n",
"too-loose\n",
"too-strict\n"
] | ---
language: "multilingual"
tags:
- Dutch
- French
- English
- Tweets
- Sentiment analysis
widget:
- text: "I really wish I could leave my house after midnight, this makes no sense!"
---
# Measuring Shifts in Attitudes Towards COVID-19 Measures in Belgium Using Multilingual BERT
[Blog post »](https://people.cs.kuleuv... | 1,363 |
ItcastAI/bert_finetuning_test | null | Entry not found | 15 |
emrecan/bert-base-multilingual-cased-allnli_tr | [
"contradiction",
"entailment",
"neutral"
] | ---
language:
- tr
tags:
- zero-shot-classification
- nli
- pytorch
pipeline_tag: zero-shot-classification
license: mit
datasets:
- nli_tr
metrics:
- accuracy
widget:
- text: "Dolar yükselmeye devam ediyor."
candidate_labels: "ekonomi, siyaset, spor"
- text: "Senaryo çok saçmaydı, beğendim diyemem."
candidate_label... | 7,067 |
lewtun/xlm-roberta-base-finetuned-marc | [
"good",
"great",
"ok",
"poor",
"terrible"
] | ---
license: mit
tags:
- generated_from_trainer
datasets:
- amazon_reviews_multi
model-index:
- name: xlm-roberta-base-finetuned-marc
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remov... | 1,423 |
lighteternal/nli-xlm-r-greek | [
"contradiction",
"entailment",
"neutral"
] | ---
language:
- el
- en
tags:
- xlm-roberta-base
datasets:
- multi_nli
- snli
- allnli_greek
metrics:
- accuracy
pipeline_tag: zero-shot-classification
widget:
- text: "Η Facebook κυκλοφόρησε τα πρώτα «έξυπνα» γυαλιά επαυξημένης πραγματικότητας."
candidate_labels: "τεχνολογία, πολιτική, αθλητισμός... | 4,773 |
maxpe/twitter-roberta-base_semeval18_emodetection | null | # Twitter-roBERTa-base_SemEval18_Emodetection
This is a Twitter-roBERTa-base model trained on ~7000 tweets in English annotated for 11 emotion categories in [SemEval-2018 Task 1: Affect in Tweets: SubTask 5: Emotion Classification](https://competitions.codalab.org/competitions/17751).
Run the classifier on the test ... | 3,356 |
mnaylor/bigbird-base-mimic-mortality | null | # BigBird for Mortality Prediction
Starting with Google's base BigBird model, we fine-tuned on binary mortality prediction in MIMIC admission notes. This
model seeks to predict whether a certain patient will expire within a given ICU stay, based on the text available upon
admission. Data prepared for this task as de... | 895 |
shiyue/roberta-large-tac08 | [
"contradiction",
"entailment",
"neutral"
] | Entry not found | 15 |
BaxterAI/SentimentClassifier | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- amazon_polarity
metrics:
- accuracy
- f1
model-index:
- name: SentimentClassifier
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: amazon_polarity
type: amazon_polarity
args: amazo... | 1,498 |
anahitapld/electra-small-dbd | null | ---
license: apache-2.0
---
| 28 |
amanbawa96/roberta_Aman | [
"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",... | Entry not found | 15 |
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