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 results.json from emonHasan01/liar-roberta: direct link, hf CLI and curl.
- Browser
- Download file 6.33 kB
-
https://huggingface.co/emonHasan01/liar-roberta/resolve/main/results.json
- Command line
-
hf download hf://emonHasan01/liar-roberta/results.json
-
curl -L -o results.json https://huggingface.co/emonHasan01/liar-roberta/resolve/main/results.json
6.33 kB
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| "roc_auc": 0.6959308468487506 | |
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| "config": { | |
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| "lr": 2e-05, | |
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| "hardware": "Tesla T4", | |
| "data_source": "hub:ucsbnlp/liar" | |
| } | |
| } |