Instructions to use hqfang/molmoact2-origami with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hqfang/molmoact2-origami with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForImageTextToText model = AutoModelForImageTextToText.from_pretrained("hqfang/molmoact2-origami", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model-00004-of-00005.safetensors from hqfang/molmoact2-origami: direct link, hf CLI and curl.
- Browser
- Download file 5 GB
-
https://huggingface.co/hqfang/molmoact2-origami/resolve/501b39f779ac6e3d68fd45cce93a4f93b6e9a952/model-00004-of-00005.safetensors
- Command line
-
hf download hf://hqfang/molmoact2-origami@501b39f779ac6e3d68fd45cce93a4f93b6e9a952/model-00004-of-00005.safetensors
-
curl -L -o model-00004-of-00005.safetensors https://huggingface.co/hqfang/molmoact2-origami/resolve/501b39f779ac6e3d68fd45cce93a4f93b6e9a952/model-00004-of-00005.safetensors
5 GB
- Xet hash:
- c2f1caf61c2ef71a98b9f43ca0eb28b2b3c59709a9e8f3a0146b2378e10fac49
- Size of remote file:
- 5 GB
- SHA256:
- 7c4d02b2174729f74b8ab17d31dfe929cea4c67aa9913ee6050cc7031f228188
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.