Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use djbrinkley97/tutorial_my_data with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use djbrinkley97/tutorial_my_data with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="djbrinkley97/tutorial_my_data")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("djbrinkley97/tutorial_my_data") model = AutoModelForSequenceClassification.from_pretrained("djbrinkley97/tutorial_my_data") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2b0b13d6ca3b81fb05c6c44e3454d5df11082775a79307b62a068fca233f5d98
- Size of remote file:
- 268 MB
- SHA256:
- 5999d6cd63abdad3ae41e8836e1cc9d33d1b6f05331b4c851e96b9b9f0b91db9
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