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
File size: 419 Bytes
4f08932 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | {
"processor_class": "ConCor1Processor",
"auto_map": {
"AutoProcessor": "processing_concor1.ConCor1Processor"
},
"num_bridge_tokens": 385,
"bridge_token_id_start": 248077,
"patch_size": 16,
"merge_size": 2,
"num_mask_upsample_blocks": 2,
"min_pixels": 1003520,
"max_pixels": 1003520,
"presence_threshold": 0.1,
"text_threshold": 0.45,
"image_threshold": 0.45,
"nms_iou_threshold": 0.5
}
|