Instructions to use PranavKeshav/upf_code_generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use PranavKeshav/upf_code_generator with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/llama-3.2-3b-instruct-bnb-4bit") model = PeftModel.from_pretrained(base_model, "PranavKeshav/upf_code_generator") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from PranavKeshav/upf_code_generator: direct link, hf CLI and curl.
- Browser
- Download file 5.56 kB
-
https://huggingface.co/PranavKeshav/upf_code_generator/resolve/main/training_args.bin
- Command line
-
hf download hf://PranavKeshav/upf_code_generator/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/PranavKeshav/upf_code_generator/resolve/main/training_args.bin
5.56 kB
- Xet hash:
- ad505acf4add4faab3173ef0f52cf008968bf5a8cf2223be283b76ea0da7a4a4
- Size of remote file:
- 5.56 kB
- SHA256:
- 74235a2ffaf25dc6c993cf52bfc3f3fcae588b27bcdc81778c2d18f86efd83e8
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