Instructions to use Changahou/Llama8B_mathinstruct_SFT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Changahou/Llama8B_mathinstruct_SFT with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/home/chenjh2/disk_chenjh/models/models/Llama-3-8b-Instruct") model = PeftModel.from_pretrained(base_model, "Changahou/Llama8B_mathinstruct_SFT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f96e8555901466d0077468a9c2b2959bca60e0843aef28580e836e937a265095
- Size of remote file:
- 6.16 kB
- SHA256:
- c540a6b99a1ec5d7d73fd1df99d521ca3c41d27e05036694816255c6fc80de60
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.