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-8500/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-8500/optimizer.pt
- Command line
-
hf download hf://trapoom555/MiniCPM-2B-Text-Embedding-cft-checkpoints/checkpoint-8500/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/trapoom555/MiniCPM-2B-Text-Embedding-cft-checkpoints/resolve/main/checkpoint-8500/optimizer.pt
11.9 MB
- Xet hash:
- 2592a3af23d5b7ae0264788f6db11c74844837476d0c99caad051c803329bd4c
- Size of remote file:
- 11.9 MB
- SHA256:
- 3079c8f7f35f8e68e0b3f3669f4421c4e9bda0dfb18553ff5501fa1a6993df6a
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