Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use alexanderfrey/instruction_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alexanderfrey/instruction_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="alexanderfrey/instruction_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("alexanderfrey/instruction_classifier") model = AutoModelForSequenceClassification.from_pretrained("alexanderfrey/instruction_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6cf1e8b5b73bdd81651421e9b84e4c075491829c7a7d1fbd7ca83533d9abbca4
- Size of remote file:
- 268 MB
- SHA256:
- 4903a77018a7316fd06adf5dab3a37c3253d7ef933d347f41c2d1db9e2336f2d
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