Instructions to use TomokiFujihara/twhin-bert-large-japanese-offensiveness-estimation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TomokiFujihara/twhin-bert-large-japanese-offensiveness-estimation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TomokiFujihara/twhin-bert-large-japanese-offensiveness-estimation", trust_remote_code=True)# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("TomokiFujihara/twhin-bert-large-japanese-offensiveness-estimation", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 461 Bytes
fbf5826 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | {
"architectures": [
"OffensivenessEstimationModel"
],
"auto_map": {
"AutoConfig": "configuration.OffensivenessEstimationConfig",
"AutoModelForSequenceClassification": "modeling.OffensivenessEstimationModel"
},
"dropout_rate": 0.1,
"language_model": "Twitter/twhin-bert-large",
"model_type": "offensiveness_estimation",
"output_class_num": 11,
"reinit_n_layers": 1,
"torch_dtype": "float32",
"transformers_version": "4.30.0"
}
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