Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use marcolatella/hate_trained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marcolatella/hate_trained with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="marcolatella/hate_trained")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("marcolatella/hate_trained") model = AutoModelForSequenceClassification.from_pretrained("marcolatella/hate_trained", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from marcolatella/hate_trained: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/marcolatella/hate_trained/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://marcolatella/hate_trained/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/marcolatella/hate_trained/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- c856ef44189f5361c19c0495908f09df77566dddc75d9f731f2edfc9a16d958b
- Size of remote file:
- 268 MB
- SHA256:
- e371d9370fc4b3793bd143d71acf51b35c63fb5cdd490cbc812c6a31cf356e7d
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