Instructions to use KalaiselvanD/lenate_model_8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KalaiselvanD/lenate_model_8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KalaiselvanD/lenate_model_8")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("KalaiselvanD/lenate_model_8") model = AutoModelForSequenceClassification.from_pretrained("KalaiselvanD/lenate_model_8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c715eb43447d1b0c2f646973ede4bcb2fbea0d11020b95d346ef2d6343a47f69
- Size of remote file:
- 46.7 MB
- SHA256:
- 2d03b88b0ccaf4b3b2e49e8723b1e0aa2bf60f91e315abdea846780584fe6c40
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