Instructions to use martin-ha/toxic-comment-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use martin-ha/toxic-comment-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="martin-ha/toxic-comment-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("martin-ha/toxic-comment-model") model = AutoModelForSequenceClassification.from_pretrained("martin-ha/toxic-comment-model") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ead0fbd5a0b2f5aa5e600be445e19c23fce379221a042a223363e4a64eab5ff9
- Size of remote file:
- 268 MB
- SHA256:
- 569aed60978bec9cdc5a90e660fe860e2eccd4f72479c1aac0c9b6c64a581e94
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