Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use zzy113/my_awesome_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zzy113/my_awesome_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="zzy113/my_awesome_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("zzy113/my_awesome_model") model = AutoModelForSequenceClassification.from_pretrained("zzy113/my_awesome_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9848f3f68d9a8617535aec6021f40a58d18195601e43cb27856b384563a171b2
- Size of remote file:
- 268 MB
- SHA256:
- 8a407f82ee7aeb48f7fdd5f617b76f0790711fe24cc2fc4767fea3a30a56224e
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