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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 162 Bytes
5eec104 | 1 2 3 4 5 6 7 8 9 10 | {
"0": "Food",
"1": "ReasonForStay",
"2": "HotelOrganisation",
"3": "Location",
"4": "GeneralUtility",
"5": "Room",
"6": "Staff",
"7": "Unknown"
} |