Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use marcolatella/hate_trained_31415 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marcolatella/hate_trained_31415 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="marcolatella/hate_trained_31415")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("marcolatella/hate_trained_31415") model = AutoModelForSequenceClassification.from_pretrained("marcolatella/hate_trained_31415") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 20df9c2c931eeb338b55798181787d66a80045c8a0c0e6f941a2e3e97c6adcf3
- Size of remote file:
- 2.93 kB
- SHA256:
- 15e5950b9a270639f33c1c472666e5237245ebb3600b918b37c2253f8d9e995f
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