Image Segmentation
Transformers
Safetensors
concor1
feature-extraction
vision-language-grounding
concept-correspondence
referring-expression-segmentation
phrase-grounding
open-vocabulary-segmentation
custom_code
Instructions to use UWGZQ/ConCor-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UWGZQ/ConCor-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="UWGZQ/ConCor-1", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("UWGZQ/ConCor-1", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 53eb1c95e358189ed552289a43d8d759198cd01114ff886ae1e546ea822a11c8
- Size of remote file:
- 885 kB
- SHA256:
- f129f1aa71773c9a9c759a2395da79411f918017b95da4224ff411e7073b11ed
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