Instructions to use facebook/sam3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/sam3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="facebook/sam3")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("facebook/sam3") model = AutoModel.from_pretrained("facebook/sam3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Request for Manual Review of SAM 3 Access Application
Hello Meta SAM 3 Team,
My access request to the SAM 3 gated repositories was rejected, but no reason was provided. I would respectfully like to request a manual review or a reset of my application.
I am Hanze Ding, a Master's student at North China Electric Power University (Beijing). My research focuses on computer vision, few-shot learning, and related areas. I intend to use SAM 3 solely for non-commercial academic research, particularly for research and evaluation involving visual perception, object segmentation, and few-shot learning tasks.
The model will be used locally for academic research and experimental evaluation only. I will fully comply with the SAM 3 license and all applicable usage restrictions, and I will not redistribute the model weights, access credentials, or any other restricted materials.
Hugging Face username: H2Ovo
Affiliation: North China Electric Power University (Beijing)
Position: Master's Student
Could you please reconsider my access request or reset my application so that I can resubmit the required information?
Thank you very much for your time and consideration.
Best regards,
Hanze Ding