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standardmodelbio
/
SMB-v1_Qwen3-8b_multi-objective

Feature Extraction
Transformers
Safetensors
English
smb_unstructured
text-generation
World Model
Patient Representation Encoder
Feature Extraction
Joint Embedding Predictive Architecture (JEPA)
custom_code
Model card Files Files and versions
xet
Community

Instructions to use standardmodelbio/SMB-v1_Qwen3-8b_multi-objective with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use standardmodelbio/SMB-v1_Qwen3-8b_multi-objective with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="standardmodelbio/SMB-v1_Qwen3-8b_multi-objective", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModelForCausalLM
    model = AutoModelForCausalLM.from_pretrained("standardmodelbio/SMB-v1_Qwen3-8b_multi-objective", trust_remote_code=True, device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle

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  • .gitattributes
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    initial commit 7 months ago
  • README.md
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  • added_tokens.json
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  • config.json
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  • merges.txt
    1.67 MB
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  • model.safetensors
    16.4 GB
    xet
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  • modeling_smb_unstructured.py
    16.3 kB
    Update modeling_smb_unstructured.py 4 months ago
  • special_tokens_map.json
    2.69 kB
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  • tokenizer_config.json
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  • vocab.json
    3.38 MB
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