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:
- f4955a366760575ea38b04fb36ce757bd2b6a53b31d2c091b008050f2386cac1
- Size of remote file:
- 1.31 GB
- SHA256:
- f58265d3a5764ff0a1c0758133beab0a51c1a29b1a97d0e09f95e160575d106e
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