Instructions to use OnMoon2/intent-classifier-bge-m3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OnMoon2/intent-classifier-bge-m3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="OnMoon2/intent-classifier-bge-m3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("OnMoon2/intent-classifier-bge-m3") model = AutoModelForSequenceClassification.from_pretrained("OnMoon2/intent-classifier-bge-m3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4786592ea7559ad79ac9adb5350927747fb7d0e28b608784f8cf9cd36906c228
- Size of remote file:
- 17.1 MB
- SHA256:
- 5df1f55d60c9705a501ab9a75550728625740741fe4be308dac4806c16b7d51d
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