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:
- d95a92dd5b07f64ec717cd9a698d12d45e34b3e417ed7dffc8e457c915aeb51c
- Size of remote file:
- 3.84 kB
- SHA256:
- 6996df450c0b525e4efb4b2b685c8e3dbe5b385122fea33741954eb2181fa041
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.