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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("marcolatella/hate_trained_31415") model = AutoModelForSequenceClassification.from_pretrained("marcolatella/hate_trained_31415", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from marcolatella/hate_trained_31415: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/marcolatella/hate_trained_31415/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://marcolatella/hate_trained_31415/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/marcolatella/hate_trained_31415/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 1e188e8ded481a6e71764631bc41539be8ee924ea348fb78ca04c667c60fd8f2
- Size of remote file:
- 268 MB
- SHA256:
- 49978a0eb7a2894db1ab484d2d4f36298f44cb4bef7563c0d9b1cf8b21df1496
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