Instructions to use Siddartha10/llama with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Siddartha10/llama with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Meta-Llama-3.1-8B-Instruct-bnb-4bit") model = PeftModel.from_pretrained(base_model, "Siddartha10/llama") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download training_args.bin from Siddartha10/llama: direct link, hf CLI and curl.
- Browser
- Download file 5.43 kB
-
https://huggingface.co/Siddartha10/llama/resolve/main/training_args.bin
- Command line
-
hf download hf://Siddartha10/llama/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Siddartha10/llama/resolve/main/training_args.bin
5.43 kB
- Xet hash:
- 460dab5d10552fa9dc24ee4e7c6d12f022f96a3d0067f6f60e53d5bdfdb0a1a2
- Size of remote file:
- 5.43 kB
- SHA256:
- 540b6ec68a37f4c562b7c940d64e83daa5ca96036cf64a8f73e3dc167f295702
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