Instructions to use AravindS373/checkpoint_book with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use AravindS373/checkpoint_book with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("AravindS373/sft_model") model = PeftModel.from_pretrained(base_model, "AravindS373/checkpoint_book") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from AravindS373/checkpoint_book: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/AravindS373/checkpoint_book/resolve/main/tokenizer.json
- Command line
-
hf download hf://AravindS373/checkpoint_book/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/AravindS373/checkpoint_book/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- d511be736037f7ae0be937adcecdafb45a8042c87316ad8e5dc0d6f6dbb812c7
- Size of remote file:
- 11.4 MB
- SHA256:
- a11add1ccce473bcd467355ba4e231ba727eee54501528658b0d6fa18112957e
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