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:
- a07f2aec7266187bffeda70fd459cd1fddb29f82fada76d60683f83de9a20cc3
- Size of remote file:
- 5.33 kB
- SHA256:
- 277832777c2a9db1aef971ac8f196deaa2eaa23a79fd742233e70941a89202a0
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