Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use agvidit1/distilbert-hate_speech18 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use agvidit1/distilbert-hate_speech18 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="agvidit1/distilbert-hate_speech18")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("agvidit1/distilbert-hate_speech18") model = AutoModelForSequenceClassification.from_pretrained("agvidit1/distilbert-hate_speech18") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a0b24fbb44a13ad345b97afdc66c87007eef385f58b094ecc733461e0edbc3c2
- Size of remote file:
- 4.66 kB
- SHA256:
- 0ee0c60740a8e2d67a7ccfe60fb597eb7554f2f518300c8958fb12ef0308a38c
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