Text Classification
Transformers
PyTorch
English
distilbert
Eval Results (legacy)
text-embeddings-inference
Instructions to use philschmid/DistilBERT-Banking77 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use philschmid/DistilBERT-Banking77 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="philschmid/DistilBERT-Banking77")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("philschmid/DistilBERT-Banking77") model = AutoModelForSequenceClassification.from_pretrained("philschmid/DistilBERT-Banking77", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Add evaluation results on banking77 dataset
Beep boop, I am a bot from Hugging Face's automatic model evaluator 👋!\ Your model has been evaluated on the [banking77](https://huggingface.co/datasets/banking77) dataset by @lewtun, using the predictions stored [here](https://huggingface.co/datasets/autoevaluate/autoeval-staging-eval-project-f87a1758-7384800).\ Accept this pull request to see the results displayed on the [Hub leaderboard](https://huggingface.co/spaces/autoevaluate/leaderboards?dataset=banking77).\ Evaluate your model on more datasets [here](https://huggingface.co/spaces/autoevaluate/model-evaluator?dataset=banking77).19f74c7
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Update README.md
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Commit From AutoTrain
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initial commit
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