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:
- 6d763547ee79f51419663b9a3192d535c9ce4f964e22c86c587ada3795b36481
- Size of remote file:
- 4.98 kB
- SHA256:
- c506e22e77e2cbebfc5cc094ca912b0f34562cb90a59703aabccd84045bda36d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.