Text Classification
Transformers
PyTorch
Core ML
Safetensors
English
bert
exbert
text-embeddings-inference
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")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ayjays132/Quantum-NeuralAdaptiveLearningSystem") model = AutoModelForSequenceClassification.from_pretrained("ayjays132/Quantum-NeuralAdaptiveLearningSystem") - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +14 -2
config.json
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"type_vocab_size": 2,
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"vocab_size": 30522
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"type_vocab_size": 2,
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"vocab_size": 30522,
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"id2label": {
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"0": "Classify",
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"1": "Positive",
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"2": "Negative"
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},
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"label2id": {
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"Classify": 0,
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"Positive": 1,
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"Negative": 2
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}
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}
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