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")# 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
Update README.md
Browse files
README.md
CHANGED
|
@@ -24,10 +24,6 @@ license: apache-2.0
|
|
| 24 |
|
| 25 |
# π Quantum-Neural Hybrid (Q-NH) Model Overview π€
|
| 26 |
|
| 27 |
-
π Quantum-Neural Hybrid (Q-NH) Model Overview π§ π
|
| 28 |
-
|
| 29 |
-
π Quantum-Neural Hybrid (Q-NH) Model Fusion π§ π
|
| 30 |
-
|
| 31 |
Embark on a cosmic computational journey with the Quantum-Neural Hybrid (Q-NH) model β a symphony of quantum magic and neural network prowess. ππ€π This futuristic oracle decodes language intricacies, processes sentiments, and offers a high-tech experience inspired by BERT but with a unique twist, merging quantum tricks and neural network wizardry for extraordinary text analysis and understanding. π§ π
|
| 32 |
|
| 33 |
model_description: >
|
|
|
|
| 24 |
|
| 25 |
# π Quantum-Neural Hybrid (Q-NH) Model Overview π€
|
| 26 |
|
|
|
|
|
|
|
|
|
|
|
|
|
| 27 |
Embark on a cosmic computational journey with the Quantum-Neural Hybrid (Q-NH) model β a symphony of quantum magic and neural network prowess. ππ€π This futuristic oracle decodes language intricacies, processes sentiments, and offers a high-tech experience inspired by BERT but with a unique twist, merging quantum tricks and neural network wizardry for extraordinary text analysis and understanding. π§ π
|
| 28 |
|
| 29 |
model_description: >
|