Instructions to use WHATX/30k-Llama3-8B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use WHATX/30k-Llama3-8B-Instruct with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("../ckpts/Meta-Llama-3-8B-Instruct") model = PeftModel.from_pretrained(base_model, "WHATX/30k-Llama3-8B-Instruct") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2e358ed7b8af38f0b42a67673b5e015cbfbc6e48140ef30a89f1a4e2558fb9f9
- Size of remote file:
- 6.84 kB
- SHA256:
- 307402fd267e1d5f5608921408e04f539b2d7cd8b53d06f2b6c2739fe534fa6d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.