Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use marcolatella/hate_trained_1234567 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marcolatella/hate_trained_1234567 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="marcolatella/hate_trained_1234567")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("marcolatella/hate_trained_1234567") model = AutoModelForSequenceClassification.from_pretrained("marcolatella/hate_trained_1234567", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from marcolatella/hate_trained_1234567: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/marcolatella/hate_trained_1234567/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://marcolatella/hate_trained_1234567/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/marcolatella/hate_trained_1234567/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 6cdd6a6700f643f0a24b5f0fad8ac7cbf4f66ffc56b1416217807a144a8115c4
- Size of remote file:
- 268 MB
- SHA256:
- 4e93452740e0ebb3717d7925d2a79bb85660fdcf9fe7950dd618e593015cb038
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