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FINAL-Bench
/
Darwin-27B-ZTC

Text Classification
Transformers
Safetensors
English
qwen3_5_text
feature-extraction
darwin
ztc
zero-token-classifier
decision-engine
typed-decisions
system-one
calibration
probabilistic-classification
Eval Results
Model card Files Files and versions
xet
Community

Instructions to use FINAL-Bench/Darwin-27B-ZTC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use FINAL-Bench/Darwin-27B-ZTC with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="FINAL-Bench/Darwin-27B-ZTC")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("FINAL-Bench/Darwin-27B-ZTC")
    model = AutoModel.from_pretrained("FINAL-Bench/Darwin-27B-ZTC", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
Darwin-27B-ZTC / autojev
20.3 kB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
SeaWolf-AI's picture
SeaWolf-AI
Clean up: public base model id in decision_config, remove internal notes and pycache
f0ffe63 verified 3 days ago
  • LICENSE
    1.07 kB
    Add files using upload-large-folder tool 3 days ago
  • __init__.py
    65 Bytes
    Add files using upload-large-folder tool 3 days ago
  • model.py
    17.3 kB
    Clean up: public base model id in decision_config, remove internal notes and pycache 3 days ago
  • types.py
    1.85 kB
    Add files using upload-large-folder tool 3 days ago