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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 574fff9f474da06d54a2c8f95c6d972fab969b148271fbad16ca3c529d2ac169
- Size of remote file:
- 2.75 kB
- SHA256:
- 15297985d714824823b83f8f7f065699353387a2b00b482aed76e73ba309bfbe
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