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phronetic-ai
/
owlet-har-1

Video Classification
Transformers
Safetensors
qwen2_5_vl
image-text-to-text
llama-factory
activity-recognition
human-action-recognition
qwen2.5-vl-3B
vision-language-model
fine-tuned
hmdb51
text-generation-inference
Model card Files Files and versions
xet
Community

Instructions to use phronetic-ai/owlet-har-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use phronetic-ai/owlet-har-1 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("video-classification", model="phronetic-ai/owlet-har-1")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForMultimodalLM
    
    processor = AutoProcessor.from_pretrained("phronetic-ai/owlet-har-1")
    model = AutoModelForMultimodalLM.from_pretrained("phronetic-ai/owlet-har-1", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
owlet-har-1
7.53 GB
Ctrl+K
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  • 1 contributor
History: 6 commits
divyansh-phronetic's picture
divyansh-phronetic
Update README.md
eb1db7e verified about 1 year ago
  • .gitattributes
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  • Modelfile
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  • README.md
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  • added_tokens.json
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  • chat_template.jinja
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  • config.json
    2.52 kB
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  • generation_config.json
    214 Bytes
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  • merges.txt
    1.67 MB
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  • model-00001-of-00002.safetensors
    5 GB
    xet
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  • model-00002-of-00002.safetensors
    2.51 GB
    xet
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  • model.safetensors.index.json
    65.4 kB
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  • preprocessor_config.json
    575 Bytes
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  • special_tokens_map.json
    613 Bytes
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  • tokenizer.json
    11.4 MB
    xet
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  • tokenizer_config.json
    4.76 kB
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  • video_preprocessor_config.json
    1.73 kB
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  • vocab.json
    2.78 MB
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