Instructions to use trapoom555/MiniCPM-2B-Text-Embedding-cft-checkpoints 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-checkpoints with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("trapoom555/MiniCPM-2B-Text-Embedding-cft-checkpoints", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-13500/optimizer.pt from trapoom555/MiniCPM-2B-Text-Embedding-cft-checkpoints: direct link, hf CLI and curl.
- Browser
- Download file 11.9 MB
-
https://huggingface.co/trapoom555/MiniCPM-2B-Text-Embedding-cft-checkpoints/resolve/main/checkpoint-13500/optimizer.pt
- Command line
-
hf download hf://trapoom555/MiniCPM-2B-Text-Embedding-cft-checkpoints/checkpoint-13500/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/trapoom555/MiniCPM-2B-Text-Embedding-cft-checkpoints/resolve/main/checkpoint-13500/optimizer.pt
11.9 MB
- Xet hash:
- b9b6650f40f0a3969ab7f74359b991fa11a5062471183dc59f66f88987336ce6
- Size of remote file:
- 11.9 MB
- SHA256:
- 3d385c1e0692635efca800d38fd5095db24b0c7021e3877422de215fccec2a74
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