Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use ishwarbb23/Q2-PHQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ishwarbb23/Q2-PHQ with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ishwarbb23/Q2-PHQ")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ishwarbb23/Q2-PHQ") model = AutoModelForSequenceClassification.from_pretrained("ishwarbb23/Q2-PHQ") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d84f6a12dcc23081baf727e8b27b1e86b45b3dfb9b2b8358a43f4c887a4a24ca
- Size of remote file:
- 268 MB
- SHA256:
- 6128980eff382c09b47ae7973fe1b1bf29f608c054243d0c5c878859ca7d0c12
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