Instructions to use quannh197/f5fb298c-df1a-4966-9c77-a5b493faeff6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use quannh197/f5fb298c-df1a-4966-9c77-a5b493faeff6 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("sethuiyer/Medichat-Llama3-8B") model = PeftModel.from_pretrained(base_model, "quannh197/f5fb298c-df1a-4966-9c77-a5b493faeff6") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3cbb63f11f705b1a71a9c9024668d12a313ac19c775f449990a6b4851196ebf2
- Size of remote file:
- 6.78 kB
- SHA256:
- 6c13a0e8d10c27a788fe0b9505734db9d2b91ee3f7391d360bce850233049a2e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.