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-5000/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-5000/optimizer.pt
- Command line
-
hf download hf://trapoom555/Phi-2-Text-Embedding-cft-checkpoints/checkpoint-5000/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/trapoom555/Phi-2-Text-Embedding-cft-checkpoints/resolve/main/checkpoint-5000/optimizer.pt
10.6 MB
- Xet hash:
- f313826092df2a6f197370aaea7083212cbadd9199f30e67bb331888d9c634a3
- Size of remote file:
- 10.6 MB
- SHA256:
- 2ee6c72873255062228ef19c59bf3cb48b23404c222597ac5d946eff880e91eb
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