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:
- c593f5922841e24e5a31d85349b0685d47ea348b77c4ed0bc784e3de38bfdaa6
- Size of remote file:
- 2.22 GB
- SHA256:
- 909167e5d951f9f74d92e407a89c2795b95edaf34a853e5ad51e195f79d3877b
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