Instructions to use warrior1127/hate_roberta_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use warrior1127/hate_roberta_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="warrior1127/hate_roberta_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("warrior1127/hate_roberta_model") model = AutoModelForSequenceClassification.from_pretrained("warrior1127/hate_roberta_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8388aaf88fb4174767b581d299bc5295a867fd784fab727b5e67a3e025ef73fa
- Size of remote file:
- 3.39 kB
- SHA256:
- 04bf9587c21c208481867b6876ac95f0eedafed4912bde37277a8c8aac9aef65
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