Instructions to use trapoom555/Phi-2-Text-Embedding-cft-checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use trapoom555/Phi-2-Text-Embedding-cft-checkpoints with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("trapoom555/Phi-2-Text-Embedding-cft-checkpoints", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-2000/optimizer.pt from trapoom555/Phi-2-Text-Embedding-cft-checkpoints: direct link, hf CLI and curl.
- Browser
- Download file 10.6 MB
-
https://huggingface.co/trapoom555/Phi-2-Text-Embedding-cft-checkpoints/resolve/main/checkpoint-2000/optimizer.pt
- Command line
-
hf download hf://trapoom555/Phi-2-Text-Embedding-cft-checkpoints/checkpoint-2000/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/trapoom555/Phi-2-Text-Embedding-cft-checkpoints/resolve/main/checkpoint-2000/optimizer.pt
10.6 MB
- Xet hash:
- a022687955027aa51e2ee0d68b341bf335173768a8d873871d945321462d26f8
- Size of remote file:
- 10.6 MB
- SHA256:
- e6c96aaaff2417bfc200ea4aead22f57013cf9097eea7e2e4d60a3d8c89148fe
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