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malusama
/
M2-Encoder-1B

Zero-Shot Image Classification
Transformers
ONNX
Chinese
English
m2_encoder
feature-extraction
multimodal
image-text-retrieval
bilingual
chinese
english
vision-language
custom-code
custom_code
Eval Results (legacy)
Model card Files Files and versions
xet
Community

Instructions to use malusama/M2-Encoder-1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use malusama/M2-Encoder-1B with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("zero-shot-image-classification", model="malusama/M2-Encoder-1B", trust_remote_code=True)
    pipe(
        "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png",
        candidate_labels=["animals", "humans", "landscape"],
    )
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("malusama/M2-Encoder-1B", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
M2-Encoder-1B / onnx
2.91 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
malusama's picture
malusama
Add ONNX exports and ONNXRuntime examples
84f82a1 verified about 2 months ago
  • image_encoder.onnx
    1.22 GB
    xet
    Add ONNX exports and ONNXRuntime examples about 2 months ago
  • text_encoder.onnx
    1.69 GB
    xet
    Add ONNX exports and ONNXRuntime examples about 2 months ago