Instructions to use IITBHUNLPLab/TEST with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IITBHUNLPLab/TEST with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="IITBHUNLPLab/TEST")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IITBHUNLPLab/TEST") model = AutoModelForSequenceClassification.from_pretrained("IITBHUNLPLab/TEST", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ee568fd867201e535046e63791aab36332860c9a94ea2f64724759bd12e959fa
- Size of remote file:
- 1.11 GB
- SHA256:
- 663b75762eeb42862a6d285d24fccbb161ca2bf12a38458a04ce9f2cd0d7b1ef
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