Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Kirie/test-bert-base-banking77 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kirie/test-bert-base-banking77 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Kirie/test-bert-base-banking77")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Kirie/test-bert-base-banking77") model = AutoModelForSequenceClassification.from_pretrained("Kirie/test-bert-base-banking77", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b5be365d3c9ed3676089ca624425c67bbf1d009eead9490ef5a1364a439df0d4
- Size of remote file:
- 438 MB
- SHA256:
- 439cb46e6bb7483b99c56d3646a44f65f88428a119a916990ae39814070acd87
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