Instructions to use warrior1127/hate_bert_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use warrior1127/hate_bert_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="warrior1127/hate_bert_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("warrior1127/hate_bert_model") model = AutoModelForSequenceClassification.from_pretrained("warrior1127/hate_bert_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7cc696150f4158920521d7d4cf3c9d6d237033afdaeed01445f19e49182d4fe1
- Size of remote file:
- 3.39 kB
- SHA256:
- a16fa1504b7d8fbf8434aeeec12111ffc1e5c3060d67c04e63607540302e7460
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