Image-to-Text
PyTorch
Safetensors
PEFT
English
remote-sensing
satellite-imagery
earth-observation
change-detection
visual-grounding
image-captioning
visual-question-answering
optical-sar-fusion
sar
multimodal
lora
Instructions to use thundercode/SatQuery with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use thundercode/SatQuery with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
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| "generated_utc": "2026-09-25T18:15:38+00:00", | |
| "generator": "release/tools/generate_model_manifest.py", | |
| "note": "Generated by reading the files. No byte count or hash is typed by hand. Backbones are NOT redistributed; they are fetched from the Hugging Face Hub, pinned by revision.", | |
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| "release_repo": "thundercode/SatQuery", | |
| "artifact_count": 6, | |
| "artifacts": [ | |
| { | |
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| "kind": "trained_head", | |
| "path": "artifacts/change/levir_change_v001/head.pt", | |
| "hf_path": "change/head.pt", | |
| "backbone": null, | |
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| "hf_path": "change_vqa/head.pt", | |
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| "hf_path": "grounding/head.pt", | |
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| "hf_path": "router/adapter.pt", | |
| "backbone": "sentence-transformers/all-MiniLM-L6-v2 (revision 1110a243fdf4)", | |
| "architecture": "task/modality adapter over frozen MiniLM embeddings (~50,822 params)", | |
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| "id": "vlm_lora_adapter", | |
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| "hf_path": "vlm/adapter_model.safetensors", | |
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