Instructions to use jrahn/llama-3-8b-claudstruct-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use jrahn/llama-3-8b-claudstruct-v2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3-8B-Instruct") model = PeftModel.from_pretrained(base_model, "jrahn/llama-3-8b-claudstruct-v2") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from jrahn/llama-3-8b-claudstruct-v2: direct link, hf CLI and curl.
- Browser
- Download file 6.46 kB
-
https://huggingface.co/jrahn/llama-3-8b-claudstruct-v2/resolve/main/training_args.bin
- Command line
-
hf download hf://jrahn/llama-3-8b-claudstruct-v2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jrahn/llama-3-8b-claudstruct-v2/resolve/main/training_args.bin
6.46 kB
- Xet hash:
- e64e5f57754423064836e89b4567d61227b24a0ea362885151c4c63b085f3266
- Size of remote file:
- 6.46 kB
- SHA256:
- 313ecaaf2979fa4223bfe586f355a60818fb1fb4b9d7c3ccb2f966acc3ae428c
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