Zero-Shot Image Classification
OpenCLIP
ONNX
English
clip
vision
aerial
drone
tracking
re-identification
Instructions to use llama-farm/llama-thunderdome-clip-aerial-vit-b16-v3-drone-fleet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- OpenCLIP
How to use llama-farm/llama-thunderdome-clip-aerial-vit-b16-v3-drone-fleet with OpenCLIP:
import open_clip model, preprocess_train, preprocess_val = open_clip.create_model_and_transforms('hf-hub:llama-farm/llama-thunderdome-clip-aerial-vit-b16-v3-drone-fleet') tokenizer = open_clip.get_tokenizer('hf-hub:llama-farm/llama-thunderdome-clip-aerial-vit-b16-v3-drone-fleet') - Notebooks
- Google Colab
- Kaggle
Upload quant_report.json with huggingface_hub
Browse files- quant_report.json +14 -0
quant_report.json
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{
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"run": {
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"net_name": "clip_aerial_vit_b_16",
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"target": "hailo10h",
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"onnx_path": "/tmp/v3-export/clip-aerial-vit-b16-v3-surgical.onnx",
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"alls_path": "/opt/thunderdome/configs/hailo/clip_vit_b_16_image_encoder_hailomz.alls",
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"calib_path": "/opt/thunderdome-project/clip-aerial/crops-pool/crops",
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"calib_count": 500,
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"hef_size_bytes": 79712256,
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"compile_seconds": 3313.784470796585
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},
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"per_layer_snr": [],
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"verdict": "COMPILE_OK_T4_PENDING"
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}
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