Instructions to use cilooor/5d19548a-5944-4486-9203-3245db7743d3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cilooor/5d19548a-5944-4486-9203-3245db7743d3 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2-7B-Instruct") model = PeftModel.from_pretrained(base_model, "cilooor/5d19548a-5944-4486-9203-3245db7743d3") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from cilooor/5d19548a-5944-4486-9203-3245db7743d3: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/cilooor/5d19548a-5944-4486-9203-3245db7743d3/resolve/main/training_args.bin
- Command line
-
hf download hf://cilooor/5d19548a-5944-4486-9203-3245db7743d3/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/cilooor/5d19548a-5944-4486-9203-3245db7743d3/resolve/main/training_args.bin
6.84 kB
- Xet hash:
- 8dfe73846b96239897059169ff5cecfdc8f0dfe1e4904cf4951237544c302d39
- Size of remote file:
- 6.84 kB
- SHA256:
- 5e6e89bdaf06af6dc2fdc33ef76f7dd91ef660839f0c433a7f1f524f5d897a5d
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