Text Classification
Transformers
ONNX
Safetensors
Transformers.js
English
roberta
fake-news-detection
misinformation
fact-checking
liar
Eval Results (legacy)
text-embeddings-inference
Instructions to use emonHasan01/liar-roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emonHasan01/liar-roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="emonHasan01/liar-roberta")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("emonHasan01/liar-roberta") model = AutoModelForSequenceClassification.from_pretrained("emonHasan01/liar-roberta", device_map="auto") - Transformers.js
How to use emonHasan01/liar-roberta with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-classification', 'emonHasan01/liar-roberta'); - Notebooks
- Google Colab
- Kaggle
Download config.json from emonHasan01/liar-roberta: direct link, hf CLI and curl.
- Browser
- Download file 795 Bytes
-
https://huggingface.co/emonHasan01/liar-roberta/resolve/main/config.json
- Command line
-
hf download hf://emonHasan01/liar-roberta/config.json
-
curl -L -o config.json https://huggingface.co/emonHasan01/liar-roberta/resolve/main/config.json
795 Bytes
| { | |
| "add_cross_attention": false, | |
| "architectures": [ | |
| "RobertaForSequenceClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": 0, | |
| "classifier_dropout": null, | |
| "dtype": "float32", | |
| "eos_token_id": 2, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "REAL", | |
| "1": "FAKE" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "is_decoder": false, | |
| "label2id": { | |
| "FAKE": 1, | |
| "REAL": 0 | |
| }, | |
| "layer_norm_eps": 1e-05, | |
| "max_position_embeddings": 514, | |
| "model_type": "roberta", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 1, | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.19.0", | |
| "type_vocab_size": 1, | |
| "use_cache": false, | |
| "vocab_size": 50265 | |
| } | |