Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use aXhyra/presentation_hate_42 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aXhyra/presentation_hate_42 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aXhyra/presentation_hate_42")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aXhyra/presentation_hate_42") model = AutoModelForSequenceClassification.from_pretrained("aXhyra/presentation_hate_42", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bb072c691c34df6c9023218272bf514292add3f235d50adde285ac6b9fc3fa06
- Size of remote file:
- 268 MB
- SHA256:
- 96438f605f0dd05b7ff23d44f6a9fbbb12e2a1002ecf4fa9fe6dd5481866dcd6
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