Instructions to use sallywww/codeLLaMA_oneStep_fuzzTargets with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use sallywww/codeLLaMA_oneStep_fuzzTargets with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("codellama/CodeLlama-7b-hf") model = PeftModel.from_pretrained(base_model, "sallywww/codeLLaMA_oneStep_fuzzTargets") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-340/rng_state.pth from sallywww/codeLLaMA_oneStep_fuzzTargets: direct link, hf CLI and curl.
- Browser
- Download file 14.2 kB
-
https://huggingface.co/sallywww/codeLLaMA_oneStep_fuzzTargets/resolve/main/checkpoint-340/rng_state.pth
- Command line
-
hf download hf://sallywww/codeLLaMA_oneStep_fuzzTargets/checkpoint-340/rng_state.pth
-
curl -L -o rng_state.pth https://huggingface.co/sallywww/codeLLaMA_oneStep_fuzzTargets/resolve/main/checkpoint-340/rng_state.pth
14.2 kB
- Xet hash:
- 0794521bba81e5a65412a47e7d9818081cf10d656524180f15b06151c9c9caff
- Size of remote file:
- 14.2 kB
- SHA256:
- fff591c203cff545ff957b8dd0a1a8f2f4a34769c838390ad53c0a683323ff1a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.