Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use osanseviero/example-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use osanseviero/example-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="osanseviero/example-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("osanseviero/example-classifier") model = AutoModelForSequenceClassification.from_pretrained("osanseviero/example-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8a39d9e928f15430f4e8c03181ed44d92b2ce15d2e72125f43bff2ec615fb081
- Size of remote file:
- 268 MB
- SHA256:
- fac677253d7b7a77aaef9cd144a66bae0929b0e9acbcd30a3fcca2cdc0e62a3e
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