Text Classification
Transformers
PyTorch
English
bert
dstc10
knowledge cluster classifier
text-embeddings-inference
Instructions to use wilsontam/bert-base-uncased-dstc10-knowledge-cluster-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wilsontam/bert-base-uncased-dstc10-knowledge-cluster-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wilsontam/bert-base-uncased-dstc10-knowledge-cluster-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wilsontam/bert-base-uncased-dstc10-knowledge-cluster-classifier") model = AutoModelForSequenceClassification.from_pretrained("wilsontam/bert-base-uncased-dstc10-knowledge-cluster-classifier") - Notebooks
- Google Colab
- Kaggle
Ctrl+K