Instructions to use skybarley/llama_custom_zero with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use skybarley/llama_custom_zero with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Meta-Llama-3.1-8B-Instruct") model = PeftModel.from_pretrained(base_model, "skybarley/llama_custom_zero") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from skybarley/llama_custom_zero: direct link, hf CLI and curl.
- Browser
- Download file 5.43 kB
-
https://huggingface.co/skybarley/llama_custom_zero/resolve/main/training_args.bin
- Command line
-
hf download hf://skybarley/llama_custom_zero/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/skybarley/llama_custom_zero/resolve/main/training_args.bin
5.43 kB
- Xet hash:
- e725219148f7129ac92b400ae09235669862bda9a3fc45bd667f6688780f296a
- Size of remote file:
- 5.43 kB
- SHA256:
- 64eb94d0f35a93c402463e0803a6ffe51b86e11865054554d9f3e225584344a8
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