Instructions to use vdos/d567726e-4959-4f05-a447-7658812e12dc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use vdos/d567726e-4959-4f05-a447-7658812e12dc with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("scb10x/llama-3-typhoon-v1.5-8b-instruct") model = PeftModel.from_pretrained(base_model, "vdos/d567726e-4959-4f05-a447-7658812e12dc") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from vdos/d567726e-4959-4f05-a447-7658812e12dc: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/vdos/d567726e-4959-4f05-a447-7658812e12dc/resolve/main/training_args.bin
- Command line
-
hf download hf://vdos/d567726e-4959-4f05-a447-7658812e12dc/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/vdos/d567726e-4959-4f05-a447-7658812e12dc/resolve/main/training_args.bin
6.84 kB
- Xet hash:
- 7d5b063e11e5f5f1769d7335dc8c0f4b584adccb120225a96907baae22c199d8
- Size of remote file:
- 6.84 kB
- SHA256:
- 925e357860d07414e5b08feb6d6f42501bc553e727e8d94d71e5345564f12bc0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.