Instructions to use windgrin/ans3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use windgrin/ans3 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/data/LLM/Llama-3.2-11B-Vision-Instruct") model = PeftModel.from_pretrained(base_model, "windgrin/ans3") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from windgrin/ans3: direct link, hf CLI and curl.
- Browser
- Download file 839 MB
-
https://huggingface.co/windgrin/ans3/resolve/main/optimizer.pt
- Command line
-
hf download hf://windgrin/ans3/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/windgrin/ans3/resolve/main/optimizer.pt
839 MB
- Xet hash:
- 137073fba6d8f1cfc7180005c570aef696eb9d9e46f336d585692b4bd4240f70
- Size of remote file:
- 839 MB
- SHA256:
- bf12ba84b2d6810bb386f72728d1c2ef3917860e20949466370602aa99923b9b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.