Instructions to use stojchet/python-sft-r64-a16-d0.05-e3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use stojchet/python-sft-r64-a16-d0.05-e3 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("deepseek-ai/deepseek-coder-1.3b-base") model = PeftModel.from_pretrained(base_model, "stojchet/python-sft-r64-a16-d0.05-e3") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from stojchet/python-sft-r64-a16-d0.05-e3: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/stojchet/python-sft-r64-a16-d0.05-e3/resolve/main/training_args.bin
- Command line
-
hf download hf://stojchet/python-sft-r64-a16-d0.05-e3/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/stojchet/python-sft-r64-a16-d0.05-e3/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- 3063766c4cb6a6004aa0920885bab8cedef2f37f4722cd1e5114f14944cf29fd
- Size of remote file:
- 5.18 kB
- SHA256:
- b0ec02287e207ce9d351c6ef38ed106ad387495c2656ccc8ead5e9db67ce7502
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