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Wfiles
/
MNLP_M2_quantized_model

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

Instructions to use Wfiles/MNLP_M2_quantized_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Wfiles/MNLP_M2_quantized_model with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="Wfiles/MNLP_M2_quantized_model")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("Wfiles/MNLP_M2_quantized_model")
    model = AutoModel.from_pretrained("Wfiles/MNLP_M2_quantized_model")
  • Notebooks
  • Google Colab
  • Kaggle
MNLP_M2_quantized_model
768 MB
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  • 1 contributor
History: 3 commits
Wfiles's picture
Wfiles
Upload tokenizer
15e4bb5 verified 12 months ago
  • .gitattributes
    1.57 kB
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  • README.md
    5.17 kB
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  • added_tokens.json
    707 Bytes
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  • config.json
    1.8 kB
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  • merges.txt
    1.67 MB
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  • model.safetensors
    752 MB
    xet
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  • special_tokens_map.json
    616 Bytes
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  • tokenizer.json
    11.4 MB
    xet
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  • tokenizer_config.json
    9.82 kB
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  • vocab.json
    2.78 MB
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