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_2.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_2.pth
- Command line
-
hf download hf://GavinChan1105/Llama-3-8B-sft-lora/checkpoint-217/rng_state_2.pth
-
curl -L -o rng_state_2.pth https://huggingface.co/GavinChan1105/Llama-3-8B-sft-lora/resolve/main/checkpoint-217/rng_state_2.pth
16 kB
- Xet hash:
- a7cbf13ecacefa5043ad1f658fd476f068581a7782451ab1b8fb1c9e87779893
- Size of remote file:
- 16 kB
- SHA256:
- f21c61b1a7e793bbdec183de3b52da90042305234bc7e5887986655cd3fc2192
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