Model Details
Full Model IDcocktailpeanut/rm
Pipeline / Taskimage-segmentation
Librarytransformers
Downloads (all-time)117.0K
Likes0
Last Modified4/12/2025
Author / Orgcocktailpeanut
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("image-segmentation", model="cocktailpeanut/rm")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerspytorchonnxsafetensorsimage-segmentationremove backgroundbackgroundbackground-removalPytorchvisionlegal liabilitytransformers.jscustom_codelicense:otherregion:us
More image-segmentation Models
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Access model files, inference API, and full documentation on Hugging Face.
Open on Hugging Face →Browse Model Files ↗← Browse All Models🤖 Task: image-segmentation
This model is designed for the image-segmentation task. Explore more models for this use case.
All image-segmentation Models →📊 Popularity
⬇ Downloads117.0K
❤️ Community Likes0
🛠️ Requirements
- →Install: pip install transformers
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.