Text Classification
Transformers
Safetensors
English
modernbert
toxicity
content-moderation
multi-label-classification
multilingual
text-embeddings-inference
Instructions to use wagesj45/multilabel-toxic-comment-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wagesj45/multilabel-toxic-comment-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wagesj45/multilabel-toxic-comment-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wagesj45/multilabel-toxic-comment-classifier") model = AutoModelForSequenceClassification.from_pretrained("wagesj45/multilabel-toxic-comment-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from wagesj45/multilabel-toxic-comment-classifier: direct link, hf CLI and curl.
- Browser
- Download file 34.4 MB
-
https://huggingface.co/wagesj45/multilabel-toxic-comment-classifier/resolve/main/tokenizer.json
- Command line
-
hf download hf://wagesj45/multilabel-toxic-comment-classifier/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/wagesj45/multilabel-toxic-comment-classifier/resolve/main/tokenizer.json
34.4 MB
- Xet hash:
- 7e0b922d78765bb4095918b864ac62b2e131101cfc8f9186dd4e28915ea610d5
- Size of remote file:
- 34.4 MB
- SHA256:
- 4379fe7f4a7af10b1ac15ffc8ae90f446f92082393699e9dd54b8c3b5ec0abad
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