Image Segmentation
Transformers
Safetensors
English
concor1
feature-extraction
vision-language
multimodal
vision-language-grounding
concept-correspondence
phrase-grounding
referring-expression-segmentation
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:
- 1df4a4f23c9b336da91ecadd3f512160361719e16062ea9ca4d4708e8ed1898e
- Size of remote file:
- 229 kB
- SHA256:
- 2f6ea9bd99c13bed37ff739d2627c512f4a8154d2d690a6484718566ab1f6504
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