Instructions to use warrior1127/hate_xlnet_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use warrior1127/hate_xlnet_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="warrior1127/hate_xlnet_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("warrior1127/hate_xlnet_model") model = AutoModelForSequenceClassification.from_pretrained("warrior1127/hate_xlnet_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ff11074362b5c6c89b3935718c52f23170ffb67082ee021ba0e5ae935cc96152
- Size of remote file:
- 1.33 GB
- SHA256:
- 73b36bd89081d8e5c509e378e09d4263a8cf386530be1fdc4a0796b0a78de56f
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