Instructions to use davidoneil/bge-m3-ft-tron with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davidoneil/bge-m3-ft-tron with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="davidoneil/bge-m3-ft-tron")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("davidoneil/bge-m3-ft-tron") model = AutoModel.from_pretrained("davidoneil/bge-m3-ft-tron", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2b1f3adb46c10577b8a1101d9d1f7435d49a3dd3d41b16538cd81e63b971a51b
- Size of remote file:
- 17.1 MB
- SHA256:
- 6e3b8957de04e3a4ed42b1a11381556f9adad8d0d502b9dd071c75f626b28f40
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