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ayjays132
/
Quantum-NeuralAdaptiveLearningSystem

Text Classification
Transformers
PyTorch
Core ML
Safetensors
English
bert
exbert
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use ayjays132/Quantum-NeuralAdaptiveLearningSystem with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use ayjays132/Quantum-NeuralAdaptiveLearningSystem with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="ayjays132/Quantum-NeuralAdaptiveLearningSystem")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("ayjays132/Quantum-NeuralAdaptiveLearningSystem")
    model = AutoModelForSequenceClassification.from_pretrained("ayjays132/Quantum-NeuralAdaptiveLearningSystem", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
Quantum-NeuralAdaptiveLearningSystem
3.16 GB
Ctrl+K
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  • 1 contributor
History: 75 commits
ayjays132's picture
ayjays132
Update config.json
b5113cb verified almost 2 years ago
  • coreml
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  • .gitattributes
    1.52 kB
    initial commit almost 3 years ago
  • README.md
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  • added_tokens.json
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  • config.json
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  • model.safetensors
    438 MB
    xet
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  • optimizer.pt
    877 MB
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  • optimizer_state.pt
    2.75 kB
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  • pytorch_model.bin
    1.31 GB
    xet
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  • rng_state.pth
    14.2 kB
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  • scheduler.pt
    1.06 kB
    xet
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  • special_tokens_map.json
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  • spiece.model
    792 kB
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  • tokenizer.json
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  • tokenizer_config.json
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  • vocab.json
    4.27 MB
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  • vocab.txt
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