modelId stringlengths 6 107 | label list | readme stringlengths 0 56.2k | readme_len int64 0 56.2k |
|---|---|---|---|
cointegrated/rubert-tiny-sentiment-balanced | [
"negative",
"neutral",
"positive"
] | ---
language: ["ru"]
tags:
- russian
- classification
- sentiment
- multiclass
widget:
- text: "Какая гадость эта ваша заливная рыба!"
---
This is the [cointegrated/rubert-tiny](https://huggingface.co/cointegrated/rubert-tiny) model fine-tuned for classification of sentiment for short Russian texts.
The problem is fo... | 2,441 |
danielhou13/longformer-finetuned_papers_v2 | null | Entry not found | 15 |
michiyasunaga/LinkBERT-base | null | ---
license: apache-2.0
language: en
datasets:
- wikipedia
- bookcorpus
tags:
- bert
- exbert
- linkbert
- feature-extraction
- fill-mask
- question-answering
- text-classification
- token-classification
---
## LinkBERT-base
LinkBERT-base model pretrained on English Wikipedia articles along with hy... | 3,543 |
unitary/unbiased-toxic-roberta | [
"toxicity",
"severe_toxicity",
"christian",
"jewish",
"muslim",
"black",
"white",
"psychiatric_or_mental_illness",
"obscene",
"identity_attack",
"insult",
"threat",
"sexual_explicit",
"male",
"female",
"homosexual_gay_or_lesbian"
] | <div align="center">
**⚠️ Disclaimer:**
The huggingface models currently give different results to the detoxify library (see issue [here](https://github.com/unitaryai/detoxify/issues/15)). For the most up to date models we recommend using the models from https://github.com/unitaryai/detoxify
# 🙊 Detoxify
## To... | 11,065 |
Xuhui/ToxDect-roberta-large | null | ---
language:
-
-
thumbnail:
tags:
-
-
-
license:
datasets:
-
-
metrics:
-
-
---
# Toxic language detection
## Model description
A toxic language detection model trained on tweets. The base model is Roberta-large. For more information,
including the **training data**, **limitations and bias**, please refer ... | 1,559 |
prajjwal1/bert-mini-mnli | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | The following model is a Pytorch pre-trained model obtained from converting Tensorflow checkpoint found in the [official Google BERT repository](https://github.com/google-research/bert). These BERT variants were introduced in the paper [Well-Read Students Learn Better: On the Importance of Pre-training Compact Models](... | 995 |
Jeevesh8/goog_bert_ft_cola-0 | null | Entry not found | 15 |
Jeevesh8/goog_bert_ft_cola-1 | null | Entry not found | 15 |
Jeevesh8/goog_bert_ft_cola-2 | null | Entry not found | 15 |
pysentimiento/bertweet-hate-speech | [
"aggressive",
"hateful",
"targeted"
] | ---
language:
- en
tags:
- twitter
- hate-speech
---
# Hate Speech detection in Spanish
## robertuito-hate-speech
Repository: [https://github.com/pysentimiento/pysentimiento/](https://github.com/finiteautomata/pysentimiento/)
Model trained with SemEval 2019 Task 5: HatEval (SubTask B) corpus for Hate Speec... | 1,398 |
Jeevesh8/goog_bert_ft_cola-3 | null | Entry not found | 15 |
cross-encoder/nli-deberta-v3-large | [
"contradiction",
"entailment",
"neutral"
] | ---
language: en
pipeline_tag: zero-shot-classification
tags:
- microsoft/deberta-v3-large
datasets:
- multi_nli
- snli
metrics:
- accuracy
license: apache-2.0
---
# Cross-Encoder for Natural Language Inference
This model was trained using [SentenceTransformers](https://sbert.net) [Cross-Encoder](https://www.sbert.net... | 2,784 |
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... | 2,648 |
IDEA-CCNL/Erlangshen-Roberta-330M-Sentiment | null | ---
language:
- zh
license: apache-2.0
tags:
- bert
- NLU
- Sentiment
inference: true
widget:
- text: "今天心情不好"
---
# Erlangshen-Roberta-330M-Semtiment, model (Chinese)，one model of [Fengshenbang-LM](https://github.com/IDEA-CCNL/Fengshenbang-LM).
We collect 8 sentiment datasets in the Chinese domain for finetune... | 1,535 |
Jeevesh8/goog_bert_ft_cola-4 | null | Entry not found | 15 |
Jeevesh8/goog_bert_ft_cola-5 | null | Entry not found | 15 |
Jeevesh8/goog_bert_ft_cola-6 | null | Entry not found | 15 |
cointegrated/rubert-base-cased-dp-paraphrase-detection | [
"entailment",
"not_entailment"
] | ---
language: ["ru"]
tags:
- sentence-similarity
- text-classification
datasets:
- merionum/ru_paraphraser
---
This is a version of paraphrase detector by DeepPavlov ([details in the documentation](http://docs.deeppavlov.ai/en/master/features/overview.html#ranking-model-docs)) ported to the `Transformers` format.
Al... | 1,510 |
ml6team/distilbert-base-german-cased-toxic-comments | [
"non_toxic",
"toxic"
] | ---
language:
- de
tags:
- distilbert
- german
- classification
datasets:
- germeval21
widget:
- text: "Das ist ein guter Punkt, so hatte ich das noch nicht betrachtet."
example_title: "Agreement (non-toxic)"
- text: "Wow, was ein geiles Spiel. Glückwunsch."
example_title: "Football (non-toxic)"
- text: "Halt deine... | 3,969 |
textattack/bert-base-uncased-RTE | null | ## TextAttack Model Card
This `bert-base-uncased` model was fine-tuned for sequence classification using TextAttack
and the glue dataset loaded using the `nlp` library. The model was fine-tuned
for 5 epochs with a batch size of 8, a learning
rate of 2e-05, and a maximum sequence length of 128.
Since this was a clas... | 622 |
Jeevesh8/goog_bert_ft_cola-7 | null | Entry not found | 15 |
ynie/bart-large-snli_mnli_fever_anli_R1_R2_R3-nli | [
"entailment",
"neutral",
"contradiction"
] | Entry not found | 15 |
Jeevesh8/goog_bert_ft_cola-8 | null | Entry not found | 15 |
howey/roberta-large-mnli | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | Entry not found | 15 |
Jeevesh8/goog_bert_ft_cola-9 | null | Entry not found | 15 |
Jeevesh8/goog_bert_ft_cola-10 | null | Entry not found | 15 |
Jeevesh8/goog_bert_ft_cola-11 | null | Entry not found | 15 |
optimum/distilbert-base-uncased-finetuned-banking77 | [
"Refund_not_showing_up",
"activate_my_card",
"age_limit",
"apple_pay_or_google_pay",
"atm_support",
"automatic_top_up",
"balance_not_updated_after_bank_transfer",
"balance_not_updated_after_cheque_or_cash_deposit",
"beneficiary_not_allowed",
"cancel_transfer",
"card_about_to_expire",
"card_acc... | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- banking77
metrics:
- accuracy
- f1
widget:
- text: Could you assist me in finding my lost card?
example_title: Example 1
- text: I found my lost card. Am I still able to use it?
example_title: Example 2
- text: "Hey, I thought my topup was all done ... | 3,616 |
Jeevesh8/goog_bert_ft_cola-12 | null | Entry not found | 15 |
l-yohai/bigbird-roberta-base-mnli | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | Entry not found | 15 |
Jeevesh8/goog_bert_ft_cola-13 | null | Entry not found | 15 |
Jeevesh8/goog_bert_ft_cola-14 | null | Entry not found | 15 |
Jeevesh8/goog_bert_ft_cola-16 | null | Entry not found | 15 |
Jeevesh8/goog_bert_ft_cola-15 | null | Entry not found | 15 |
j-hartmann/purchase-intention-english-roberta-large | [
"no",
"yes"
] | ---
language: "en"
tags:
- roberta
- sentiment
- twitter
widget:
- text: "This looks tasty. Where can I buy it??"
- text: "Now I want this, too."
- text: "You look great today!"
- text: "I just love spring and sunshine!"
---
This RoBERTa-based model can classify *expressed purchase intentions* in English language te... | 1,427 |
deepset/bert-base-german-cased-hatespeech-GermEval18Coarse | [
"OFFENSE",
"OTHER"
] | ---
license: cc-by-4.0
---
This is a German BERT v1 (https://deepset.ai/german-bert) trained to do hate speech detection on the GermEval18Coarse dataset | 153 |
Jeevesh8/goog_bert_ft_cola-17 | null | Entry not found | 15 |
valurank/distilroberta-hatespeech | [
"HATE",
"NOT_HATE"
] | ---
license: other
tags:
- generated_from_trainer
model-index:
- name: distilroberta-hatespeech
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. -->
# distilroberta-h... | 1,625 |
Jeevesh8/goog_bert_ft_cola-18 | null | Entry not found | 15 |
Jeevesh8/goog_bert_ft_cola-20 | null | Entry not found | 15 |
Jeevesh8/goog_bert_ft_cola-19 | null | Entry not found | 15 |
valurank/distilroberta-proppy | [
"no_prop",
"prop"
] | ---
license: other
tags:
- generated_from_trainer
model-index:
- name: distilroberta-proppy
results: []
---
# distilroberta-proppy
This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the proppy corpus.
It achieves the following results on the evaluation set:
- L... | 2,133 |
valurank/distilroberta-offensive | [
"NOT_OFFENSIVE",
"OFFENSIVE"
] | ---
license: other
tags:
- generated_from_trainer
model-index:
- name: distilroberta-offensive
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. -->
# distilroberta-of... | 1,736 |
Jeevesh8/goog_bert_ft_cola-21 | null | Entry not found | 15 |
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... | 741 |
Jeevesh8/goog_bert_ft_cola-22 | null | Entry not found | 15 |
Harshveer/autonlp-formality_scoring_2-32597818 | [
"target"
] | ---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
datasets:
- Harshveer/autonlp-data-formality_scoring_2
co2_eq_emissions: 8.655894631203154
---
# Model Trained Using AutoNLP
- Problem type: Single Column Regression
- Model ID: 32597818
- CO2 Emissions (in grams): 8.655894631203154
## Validation Met... | 1,201 |
Bhumika/roberta-base-finetuned-sst2 | null | ---
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: roberta-base-finetuned-sst2
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: sst2
metrics:
- name: Accuracy
type: accu... | 1,755 |
Jeevesh8/goog_bert_ft_cola-23 | null | Entry not found | 15 |
Jeevesh8/goog_bert_ft_cola-24 | null | Entry not found | 15 |
valurank/distilroberta-propaganda-2class | [
"No_Prop",
"Prop"
] | ---
license: other
tags:
- generated_from_trainer
model-index:
- name: distilroberta-propaganda-2class
results: []
---
# distilroberta-propaganda-2class
This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the QCRI propaganda dataset.
It achieves the following r... | 2,172 |
w11wo/indonesian-roberta-base-indolem-sentiment-classifier-fold-0 | null | ---
language: id
tags:
- indonesian-roberta-base-indolem-sentiment-classifier-fold-0
license: mit
datasets:
- indolem
widget:
- text: "Pelayanan hotel ini sangat baik."
---
## Indonesian RoBERTa Base IndoLEM Sentiment Classifier
Indonesian RoBERTa Base IndoLEM Sentiment Classifier is a sentiment-text-classifica... | 4,195 |
Jeevesh8/goog_bert_ft_cola-25 | null | Entry not found | 15 |
salesken/xlm-roberta-base-finetuned-mnli-cross-lingual-transfer | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | ---
datasets:
- mnli
- xnli
tags:
- sentence-similarity
- transformers
- text-classification
- zero-shot-classification
- salesken
- hindi
- cross-lingual
inference: false
---
# XLM-R Base
A multilingual model is pre-trained on text coming from a mix of languages. We will look at a multilingual model called XLM-R fro... | 7,994 |
Jeevesh8/goog_bert_ft_cola-26 | null | Entry not found | 15 |
assemblyai/bert-large-uncased-sst2 | null | # BERT-Large-Uncased for Sentiment Analysis
This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) originally released in ["BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding"](https://arxiv.org/abs/1810.04805) and trained on the [Stanford Sen... | 1,758 |
Jeevesh8/goog_bert_ft_cola-27 | null | Entry not found | 15 |
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... | 709 |
Jeevesh8/goog_bert_ft_cola-28 | null | Entry not found | 15 |
Jeevesh8/goog_bert_ft_cola-29 | null | Entry not found | 15 |
fabriceyhc/bert-base-uncased-imdb | null | ---
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... | 1,993 |
digitalepidemiologylab/covid-twitter-bert-v2-mnli | [
"contradiction",
"neutral",
"entailment"
] | ---
language:
- en
thumbnail: https://raw.githubusercontent.com/digitalepidemiologylab/covid-twitter-bert/master/images/COVID-Twitter-BERT_small.png
tags:
- Twitter
- COVID-19
- text-classification
- pytorch
- tensorflow
- bert
license: mit
datasets:
- mnli
pipeline_tag: zero-shot-classification
widget:
- text: To stop... | 3,085 |
Jeevesh8/goog_bert_ft_cola-30 | null | Entry not found | 15 |
Jeevesh8/goog_bert_ft_cola-31 | null | Entry not found | 15 |
Jeevesh8/goog_bert_ft_cola-32 | null | Entry not found | 15 |
Skoltech/russian-inappropriate-messages | null | ---
language:
- ru
tags:
- toxic comments classification
licenses:
- cc-by-nc-sa
---
## General concept of the model
#### Proposed usage
The **'inappropriateness'** substance we tried to collect in the dataset and detect with the model **is NOT a substitution of toxicity**, it is rather a derivative of toxicity. S... | 6,383 |
bhadresh-savani/distilbert-base-uncased-go-emotion | [
"admiration",
"amusement",
"anger",
"annoyance",
"approval",
"caring",
"confusion",
"curiosity",
"desire",
"disappointment",
"disapproval",
"disgust",
"embarrassment",
"excitement",
"fear",
"gratitude",
"grief",
"joy",
"love",
"nervousness",
"neutral",
"optimism",
"pride"... | ---
language:
- en
thumbnail: https://avatars3.githubusercontent.com/u/32437151?s=460&u=4ec59abc8d21d5feea3dab323d23a5860e6996a4&v=4
tags:
- text-classification
- go-emotion
- pytorch
license: apache-2.0
datasets:
- go_emotions
metrics:
- Accuracy
---
# Distilbert-Base-Uncased-Go-Emotion
## Model description:
**Not ... | 888 |
Jeevesh8/goog_bert_ft_cola-33 | null | Entry not found | 15 |
Jeevesh8/goog_bert_ft_cola-34 | null | Entry not found | 15 |
cointegrated/roberta-base-formality | null | Entry not found | 15 |
Jeevesh8/goog_bert_ft_cola-35 | null | Entry not found | 15 |
sshleifer/tiny-distilbert-base-uncased-finetuned-sst-2-english | [
"NEGATIVE",
"POSITIVE"
] | Entry not found | 15 |
responsibility-framing/predict-perception-bert-blame-object | [
"LABEL_0"
] | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: predict-perception-bert-blame-object
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. -->
# predi... | 7,718 |
responsibility-framing/predict-perception-bert-cause-human | [
"LABEL_0"
] | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: predict-perception-bert-cause-human
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. -->
# predic... | 9,268 |
responsibility-framing/predict-perception-xlmr-cause-human | [
"LABEL_0"
] | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: predict-perception-xlmr-cause-human
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. -->
# predic... | 9,298 |
Jeevesh8/goog_bert_ft_cola-36 | null | Entry not found | 15 |
responsibility-framing/predict-perception-bert-focus-concept | [
"LABEL_0"
] | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: predict-perception-bert-focus-concept
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. -->
# pred... | 10,393 |
Jeevesh8/goog_bert_ft_cola-37 | null | Entry not found | 15 |
responsibility-framing/predict-perception-bert-cause-object | [
"LABEL_0"
] | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: predict-perception-bert-cause-object
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. -->
# predi... | 10,589 |
dmis-lab/biobert-base-cased-v1.1-mnli | [
"LABEL_0",
"LABEL_1"
] | Entry not found | 15 |
responsibility-framing/predict-perception-bert-blame-none | [
"LABEL_0"
] | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: predict-perception-bert-blame-none
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. -->
# predict... | 7,449 |
responsibility-framing/predict-perception-bert-cause-concept | [
"LABEL_0"
] | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: predict-perception-bert-cause-concept
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. -->
# pred... | 11,185 |
responsibility-framing/predict-perception-bert-cause-none | [
"LABEL_0"
] | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: predict-perception-bert-cause-none
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. -->
# predict... | 10,719 |
Jeevesh8/goog_bert_ft_cola-38 | null | Entry not found | 15 |
responsibility-framing/predict-perception-bert-blame-assassin | [
"LABEL_0"
] | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: predict-perception-bert-blame-assassin
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. -->
# pre... | 7,789 |
responsibility-framing/predict-perception-bert-focus-object | [
"LABEL_0"
] | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: predict-perception-bert-focus-object
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. -->
# predi... | 7,983 |
responsibility-framing/predict-perception-xlmr-blame-none | [
"LABEL_0"
] | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: predict-perception-xlmr-blame-none
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. -->
# predict... | 7,415 |
responsibility-framing/predict-perception-xlmr-cause-concept | [
"LABEL_0"
] | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: predict-perception-xlmr-cause-concept
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. -->
# pred... | 11,183 |
responsibility-framing/predict-perception-bert-blame-victim | [
"LABEL_0"
] | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: predict-perception-bert-blame-victim
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. -->
# predi... | 7,752 |
responsibility-framing/predict-perception-bert-blame-concept | [
"LABEL_0"
] | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: predict-perception-bert-blame-concept
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. -->
# pred... | 10,128 |
responsibility-framing/predict-perception-bert-focus-assassin | [
"LABEL_0"
] | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: predict-perception-bert-focus-assassin
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. -->
# pre... | 8,118 |
responsibility-framing/predict-perception-bert-focus-victim | [
"LABEL_0"
] | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: predict-perception-bert-focus-victim
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. -->
# predi... | 8,015 |
responsibility-framing/predict-perception-xlmr-blame-object | [
"LABEL_0"
] | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: predict-perception-xlmr-blame-object
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. -->
# predi... | 7,716 |
responsibility-framing/predict-perception-xlmr-blame-concept | [
"LABEL_0"
] | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: predict-perception-xlmr-blame-concept
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. -->
# pred... | 10,062 |
responsibility-framing/predict-perception-xlmr-cause-object | [
"LABEL_0"
] | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: predict-perception-xlmr-cause-object
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. -->
# predi... | 10,587 |
responsibility-framing/predict-perception-xlmr-focus-victim | [
"LABEL_0"
] | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: predict-perception-xlmr-focus-victim
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. -->
# predi... | 7,981 |
responsibility-framing/predict-perception-xlmr-focus-concept | [
"LABEL_0"
] | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: predict-perception-xlmr-focus-concept
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. -->
# pred... | 10,359 |
Jeevesh8/goog_bert_ft_cola-39 | null | Entry not found | 15 |
responsibility-framing/predict-perception-xlmr-blame-victim | [
"LABEL_0"
] | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: predict-perception-xlmr-blame-victim
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. -->
# predi... | 7,719 |
responsibility-framing/predict-perception-xlmr-blame-assassin | [
"LABEL_0"
] | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: predict-perception-xlmr-blame-assassin
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. -->
# pre... | 7,755 |
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