Text Classification
Transformers
PyTorch
English
bert
Trained with AutoTrain
Eval Results (legacy)
text-embeddings-inference
Instructions to use philschmid/BERT-Banking77 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use philschmid/BERT-Banking77 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="philschmid/BERT-Banking77")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("philschmid/BERT-Banking77") model = AutoModelForSequenceClassification.from_pretrained("philschmid/BERT-Banking77") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
4580c6c | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:f7b13360b32a24cb5de1fd24dced21184a9e64b9450d01e26cfe9c78bf335b26
size 438249901
|