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_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-434/rng_state_2.pth
- Command line
-
hf download hf://GavinChan1105/Llama-3-8B-sft-lora/checkpoint-434/rng_state_2.pth
-
curl -L -o rng_state_2.pth https://huggingface.co/GavinChan1105/Llama-3-8B-sft-lora/resolve/main/checkpoint-434/rng_state_2.pth
16 kB
- Xet hash:
- 4fcf82dc137fdd21a1efd782e0be6c24d49d0bf4e1b71b8b07fc3cb8b41299b7
- Size of remote file:
- 16 kB
- SHA256:
- 896febe768e17bae5022a95960c041f6425783774ec8859d99d3b149063b1bf9
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