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andrebadini
/
Qwen3-Embedding-4B-NVFP4

Feature Extraction
Transformers
Safetensors
qwen3
text-generation
embeddings
nvfp4
blackwell
compressed-tensors
text-embeddings-inference
8-bit precision
Model card Files Files and versions
xet
Community

Instructions to use andrebadini/Qwen3-Embedding-4B-NVFP4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use andrebadini/Qwen3-Embedding-4B-NVFP4 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="andrebadini/Qwen3-Embedding-4B-NVFP4")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("andrebadini/Qwen3-Embedding-4B-NVFP4")
    model = AutoModelForCausalLM.from_pretrained("andrebadini/Qwen3-Embedding-4B-NVFP4")
  • Notebooks
  • Google Colab
  • Kaggle
Qwen3-Embedding-4B-NVFP4
2.83 GB
Ctrl+K
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  • 1 contributor
History: 2 commits
andrebadini's picture
andrebadini
Upload NVFP4 quantized Qwen3-Embedding-4B
15f4e85 verified 17 days ago
  • .gitattributes
    1.57 kB
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  • README.md
    2.62 kB
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  • chat_template.jinja
    2.43 kB
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  • config.json
    2.97 kB
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  • generation_config.json
    117 Bytes
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  • model.safetensors
    2.82 GB
    xet
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  • recipe.yaml
    170 Bytes
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  • tokenizer.json
    11.4 MB
    xet
    Upload NVFP4 quantized Qwen3-Embedding-4B 17 days ago
  • tokenizer_config.json
    378 Bytes
    Upload NVFP4 quantized Qwen3-Embedding-4B 17 days ago