Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use HCKLab/BiBert-Classification-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HCKLab/BiBert-Classification-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HCKLab/BiBert-Classification-1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HCKLab/BiBert-Classification-1") model = AutoModelForSequenceClassification.from_pretrained("HCKLab/BiBert-Classification-1") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
9523fd5 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:eca4768ee408a71175056602959f8b718b47c72d92a882bdbdd0c9d774e056dc
size 669512045
|