Model Details
Full Model IDshi-labs/oneformer_coco_swin_large
Pipeline / Taskimage-segmentation
Librarytransformers
Downloads (all-time)64.3K
Likes8
Last Modified1/19/2023
Author / Orgshi-labs
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="shi-labs/oneformer_coco_swin_large")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerspytorchoneformervisionimage-segmentationdataset:ydshieh/coco_dataset_scriptarxiv:2211.06220license:mitendpoints_compatibledeploy:azureregion:us
More image-segmentation Models
See all →🚀 Use This Model
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
⬇ Downloads64.3K
❤️ Community Likes8
🛠️ 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.