Image Segmentation
BEN2
ONNX
Safetensors
PyTorch
BEN2
background-remove
mask-generation
Dichotomous image segmentation
background remove
foreground
background
remove background
model_hub_mixin
pytorch_model_hub_mixin
background removal
background-removal
Instructions to use PramaLLC/BEN2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- BEN2
How to use PramaLLC/BEN2 with BEN2:
import requests from PIL import Image from ben2 import AutoModel url = "https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg" image = Image.open(requests.get(url, stream=True).raw) model = AutoModel.from_pretrained("PramaLLC/BEN2") model.to("cuda").eval() foreground = model.inference(image) - Notebooks
- Google Colab
- Kaggle
Commit History
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add AIBOM
Verified signatureDear PramaLLC, We are a group of researchers investigating the usefulness of sharing AIBOMs (Artificial Intelligence Bill of Materials) to document AI models and to improve transparency in AI model supply chains. AIBOMs are machine-readable, structured inventories of components—such as datasets and models—used in the development of AI-powered systems. We would like to emphasize that we have no financial or competing interests related to AIBOMs. Our sole interest is to advance the collective understanding of AIBOMs within both academia and industry. As part of this effort, we are contributing to randomly selected open and popular models on Hugging Face (like yours) and are happy to offer support to you and the maintainers of your model if needed. Based on your model card (and some configuration information available in Hugging Face), we generated the AIBOM according to the CyclonDX (v1.6) standard (see https://cyclonedx.org/docs/1.6/json/). This AIBOM is generated as a JSON file by …eb06ee4
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Verified signature- integrate with huggingface (5ad69f0c63c1820bf9c9486fac0127ded199c980) Co-authored-by: Hafedh Hichri <not-lain@users.noreply.huggingface.co>19d0d22
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