Instructions to use entfane/Toxic_Llama8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use entfane/Toxic_Llama8B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="entfane/Toxic_Llama8B")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("entfane/Toxic_Llama8B") model = AutoModelForSequenceClassification.from_pretrained("entfane/Toxic_Llama8B") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5a77c47cfd878930db4e9faf5db4c30a7cfbc577f13edad96c6c3abc2722e7c5
- Size of remote file:
- 17.2 MB
- SHA256:
- 90883524dbec2e8c465564ac46b4e5298235668a5cf8523690f06f45f51646fe
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