Visual Question Answering
Transformers
Safetensors
English
panovlm_decision
feature-extraction
panovlm
decision-model
calibration
fastvit
linear-attention
custom_code
Instructions to use PanocularAI/PanoVLD-500M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PanocularAI/PanoVLD-500M with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "visual-question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("visual-question-answering", model="PanocularAI/PanoVLD-500M", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("PanocularAI/PanoVLD-500M", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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| VLFeedback | 2,000 | 54.3% | 0.035 | 1.15 |
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| AVA | 1,000 | 84.7% | 0.323 | 0.76 |
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## License
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The weights are released under **CC BY-NC-SA 4.0**.
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| VLFeedback | 2,000 | 54.3% | 0.035 | 1.15 |
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| RichHF-18K | 1,990 | 55.5% | 0.071 | 0.98 |
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| AVA | 1,000 | 84.7% | 0.323 | 0.76 |
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| CrisisMMD | 529 | 73.7% | 0.110 | 0.68 |
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