Image Segmentation
Transformers
Safetensors
English
prima
text-generation
computer-vision
multi-image-reasoning
pixel-grounding
vision-language
custom-code
custom_code
Instructions to use kanguyen-vn/PRIMA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kanguyen-vn/PRIMA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="kanguyen-vn/PRIMA", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("kanguyen-vn/PRIMA", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
Today
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Keep the PRIMA architecture and verify prediction resume provenance
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Use one paper evaluator and clarify metric coverage
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Remove debug instrumentation and rename the M4Seg dataset adapter
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Include clean PRIMA code and evaluator; document metrics, initialization, and MIT contributions
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