Instructions to use trapoom555/Gemma-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/Gemma-2B-Text-Embedding-cft-checkpoints with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("trapoom555/Gemma-2B-Text-Embedding-cft-checkpoints", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-6000/training_args.bin from trapoom555/Gemma-2B-Text-Embedding-cft-checkpoints: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/trapoom555/Gemma-2B-Text-Embedding-cft-checkpoints/resolve/main/checkpoint-6000/training_args.bin
- Command line
-
hf download hf://trapoom555/Gemma-2B-Text-Embedding-cft-checkpoints/checkpoint-6000/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/trapoom555/Gemma-2B-Text-Embedding-cft-checkpoints/resolve/main/checkpoint-6000/training_args.bin
4.98 kB
- Xet hash:
- b7fae4d40db4cfa1ac72c0d743b46d9a0969cef994e5bb434e0913a8043f140f
- Size of remote file:
- 4.98 kB
- SHA256:
- 1f13496797d6aaea4e21d2f2de24d7b2ec5d76cf72e27733fa08925121d91fd2
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