Instructions to use GavinChan1105/Llama-3-8B-sft-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use GavinChan1105/Llama-3-8B-sft-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.1-8B") model = PeftModel.from_pretrained(base_model, "GavinChan1105/Llama-3-8B-sft-lora") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-217/rng_state_5.pth from GavinChan1105/Llama-3-8B-sft-lora: direct link, hf CLI and curl.
- Browser
- Download file 16 kB
-
https://huggingface.co/GavinChan1105/Llama-3-8B-sft-lora/resolve/main/checkpoint-217/rng_state_5.pth
- Command line
-
hf download hf://GavinChan1105/Llama-3-8B-sft-lora/checkpoint-217/rng_state_5.pth
-
curl -L -o rng_state_5.pth https://huggingface.co/GavinChan1105/Llama-3-8B-sft-lora/resolve/main/checkpoint-217/rng_state_5.pth
16 kB
- Xet hash:
- 261bd53438d029ecaf84334f1378223ec88e953aba0e7f896d2aef3475b761b0
- Size of remote file:
- 16 kB
- SHA256:
- 864ea2379cc907eb4189c52706cb978150d9c26e18abf74679590729a8f0c8e8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.