Instructions to use tibaf/embeddinggemma-300m-litert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT
How to use tibaf/embeddinggemma-300m-litert with LiteRT:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
EmbeddingGemma 300M (LiteRT) โ Memoyad mirror
Unmodified copies of the following files from litert-community/embeddinggemma-300m, hosted so the Memoyad app has a stable download source.
| File | Size (bytes) | SHA-256 |
|---|---|---|
embeddinggemma-300M_seq256_mixed-precision.tflite |
179131736 | 37115ef7bff76cd37dd86abe503ff511b1032bf85fc624a85c49c84899e92bc5 |
sentencepiece_for_embeddinggemma.model |
4683319 | d6daa52d93d7aad10e8388bd526c4e501d914b47177398d1d9621f1fe48438c7 |
No weights, graphs or tokenizer data were changed.
License
Gemma is provided under and subject to the Gemma Terms of Use found at ai.google.dev/gemma/terms
A copy of the terms is in GEMMA_TERMS_OF_USE.md. Use of this model is subject
to the Gemma Prohibited Use Policy, which is part of
those terms. By downloading or using these files you agree to them.
Credits
EmbeddingGemma was developed by Google DeepMind. LiteRT conversion by the LiteRT community (Google AI Edge). This repository is not affiliated with or endorsed by Google.
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Base model
google/embeddinggemma-300m