Instructions to use trapoom555/MiniCPM-2B-Text-Embedding-cft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use trapoom555/MiniCPM-2B-Text-Embedding-cft with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("trapoom555/MiniCPM-2B-Text-Embedding-cft", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 264f7602299baa259827e9f01005b4ba841ce103ca7f511679016863f93f935c
- Size of remote file:
- 5.92 MB
- SHA256:
- 98a6673650f0341a09b85b29df958305686f39a2c562102c86dbf0ba9443f436
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