Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Multilabel
text-embeddings-inference
Instructions to use DunnBC22/bert-base-uncased-Research_Articles_Multilabel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DunnBC22/bert-base-uncased-Research_Articles_Multilabel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DunnBC22/bert-base-uncased-Research_Articles_Multilabel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DunnBC22/bert-base-uncased-Research_Articles_Multilabel") model = AutoModelForSequenceClassification.from_pretrained("DunnBC22/bert-base-uncased-Research_Articles_Multilabel") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1 opened over 2 years ago
by
SFconvertbot