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
| { | |
| "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" | |
| } | |