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-434/rng_state_4.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-434/rng_state_4.pth
- Command line
-
hf download hf://GavinChan1105/Llama-3-8B-sft-lora/checkpoint-434/rng_state_4.pth
-
curl -L -o rng_state_4.pth https://huggingface.co/GavinChan1105/Llama-3-8B-sft-lora/resolve/main/checkpoint-434/rng_state_4.pth
16 kB
- Xet hash:
- f06bfba948426cdd731cf7fc6960dd5af81e5f0f6efeb82fbddb45d4c62d7009
- Size of remote file:
- 16 kB
- SHA256:
- e1f27d227a20dc320ac283e0938fb2f6e5b475829a583f8c44d1a16a8c828307
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.