Instructions to use smjain/amazon_vlm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use smjain/amazon_vlm with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2-VL-7B-Instruct") model = PeftModel.from_pretrained(base_model, "smjain/amazon_vlm") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from smjain/amazon_vlm: direct link, hf CLI and curl.
- Browser
- Download file 20.3 MB
-
https://huggingface.co/smjain/amazon_vlm/resolve/main/optimizer.pt
- Command line
-
hf download hf://smjain/amazon_vlm/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/smjain/amazon_vlm/resolve/main/optimizer.pt
20.3 MB
- Xet hash:
- ea43377079c88ef901d8722a442cac3394a9bff8ab076e49e90990a245b565c9
- Size of remote file:
- 20.3 MB
- SHA256:
- 7151715c23fe43b913ce051c875676177b7ccfe84e9ddb0cd52d0ad3845b2175
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.