Instructions to use dada22231/1a9fd1cb-c80e-4653-a3ef-2225f77125b7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/1a9fd1cb-c80e-4653-a3ef-2225f77125b7 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("dltjdgh0928/test_instruction") model = PeftModel.from_pretrained(base_model, "dada22231/1a9fd1cb-c80e-4653-a3ef-2225f77125b7") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.model from dada22231/1a9fd1cb-c80e-4653-a3ef-2225f77125b7: direct link, hf CLI and curl.
- Browser
- Download file 493 kB
-
https://huggingface.co/dada22231/1a9fd1cb-c80e-4653-a3ef-2225f77125b7/resolve/main/tokenizer.model
- Command line
-
hf download hf://dada22231/1a9fd1cb-c80e-4653-a3ef-2225f77125b7/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/dada22231/1a9fd1cb-c80e-4653-a3ef-2225f77125b7/resolve/main/tokenizer.model
493 kB
- Xet hash:
- 32726c94d96b1a5c442963faa3a900decf397fe67b5c530097a9f8b2506c63b6
- Size of remote file:
- 493 kB
- SHA256:
- dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
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