Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use marcolatella/hate_trained_42 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marcolatella/hate_trained_42 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="marcolatella/hate_trained_42")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("marcolatella/hate_trained_42") model = AutoModelForSequenceClassification.from_pretrained("marcolatella/hate_trained_42", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from marcolatella/hate_trained_42: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/marcolatella/hate_trained_42/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://marcolatella/hate_trained_42/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/marcolatella/hate_trained_42/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 8c09d7ade596f19759529d5ad6a0868ca28afc56efb2b280515a89a63254a921
- Size of remote file:
- 268 MB
- SHA256:
- 94300f63e12bbe5a725071a2c6ab3b6e41978d1495b9679950508bf1b2bc6371
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