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_0.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_0.pth
- Command line
-
hf download hf://GavinChan1105/Llama-3-8B-sft-lora/checkpoint-434/rng_state_0.pth
-
curl -L -o rng_state_0.pth https://huggingface.co/GavinChan1105/Llama-3-8B-sft-lora/resolve/main/checkpoint-434/rng_state_0.pth
16 kB
- Xet hash:
- 16e5c9a42576713863d00b01d8aa800866ae698073bea2582f9da2e473336447
- Size of remote file:
- 16 kB
- SHA256:
- 78d3f197f6c6558fa8056324f1563ab9e957255f5a1a959362aa4eed7a9545db
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