Instructions to use philschmid/quantized-distilbert-banking77 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use philschmid/quantized-distilbert-banking77 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="philschmid/quantized-distilbert-banking77")# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("philschmid/quantized-distilbert-banking77", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f4e6284fb7ff2e2ba91aa2b953a635c8e9c51104afe30249bba6be44f30a8bab
- Size of remote file:
- 141 MB
- SHA256:
- 8451c0b112f416642c82349cba6677ce774587fff19d3e23151d00858f129e77
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