Instructions to use Tobias/bert-base-uncased_English_MultiLable_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tobias/bert-base-uncased_English_MultiLable_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Tobias/bert-base-uncased_English_MultiLable_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Tobias/bert-base-uncased_English_MultiLable_classification") model = AutoModelForSequenceClassification.from_pretrained("Tobias/bert-base-uncased_English_MultiLable_classification") - Notebooks
- Google Colab
- Kaggle
| { | |
| "0": "Food", | |
| "1": "ReasonForStay", | |
| "2": "HotelOrganisation", | |
| "3": "Location", | |
| "4": "GeneralUtility", | |
| "5": "Room", | |
| "6": "Staff", | |
| "7": "Unknown" | |
| } |