Instructions to use fathyshalab/bert-uncased-massive-intent-classification-banking-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fathyshalab/bert-uncased-massive-intent-classification-banking-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fathyshalab/bert-uncased-massive-intent-classification-banking-1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fathyshalab/bert-uncased-massive-intent-classification-banking-1") model = AutoModelForSequenceClassification.from_pretrained("fathyshalab/bert-uncased-massive-intent-classification-banking-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d9cd1200e40ea1b2683a80402a0d28e517bde670e5a4cf4757c26eb4ecc3a97d
- Size of remote file:
- 3.44 kB
- SHA256:
- 32c759e8675dfd3ba0456aa249db511b52ae2cd2f2abca909feeb8cc002e4862
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