Instructions to use sidd272/Distilbert_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sidd272/Distilbert_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sidd272/Distilbert_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sidd272/Distilbert_model") model = AutoModelForSequenceClassification.from_pretrained("sidd272/Distilbert_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from sidd272/Distilbert_model: direct link, hf CLI and curl.
- Browser
- Download file 4.6 kB
-
https://huggingface.co/sidd272/Distilbert_model/resolve/main/training_args.bin
- Command line
-
hf download hf://sidd272/Distilbert_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/sidd272/Distilbert_model/resolve/main/training_args.bin
4.6 kB
- Xet hash:
- eae39408d046c8457f6a36ae88c418ba4d44179918a3164aafec4d790b6b31e1
- Size of remote file:
- 4.6 kB
- SHA256:
- 7df1fca6b7981ddfbe8e5657717e3a281caae931efc9fd8979eb254c9f53bf7c
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