Instructions to use prxy5608/89a42b8f-9a84-4f18-81b6-9e8b3222f798 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use prxy5608/89a42b8f-9a84-4f18-81b6-9e8b3222f798 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM-135M-Instruct") model = PeftModel.from_pretrained(base_model, "prxy5608/89a42b8f-9a84-4f18-81b6-9e8b3222f798") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from prxy5608/89a42b8f-9a84-4f18-81b6-9e8b3222f798: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/prxy5608/89a42b8f-9a84-4f18-81b6-9e8b3222f798/resolve/main/training_args.bin
- Command line
-
hf download hf://prxy5608/89a42b8f-9a84-4f18-81b6-9e8b3222f798/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/prxy5608/89a42b8f-9a84-4f18-81b6-9e8b3222f798/resolve/main/training_args.bin
6.84 kB
- Xet hash:
- 27058d0dbd3b21820f65bef08bfb6e9a504bf6d34b3b8a8397a0a5bd0bbdfb7b
- Size of remote file:
- 6.84 kB
- SHA256:
- 2fc47c0607af378e97f4dbb89091aea8a844ee9d9de9c4fe95f7634f7f6ab27d
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