# 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.jsEmbeddingGemma (LiteRT): Memoyad mirror
These are unmodified copies of EmbeddingGemma LiteRT files. They are hosted here so the Memoyad app always has a stable download source.
EmbeddingGemma 300M
Source: litert-community/embeddinggemma-300m
| 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. The app pins each download to a commit of this repository and checks the SHA-256 above. Adding files here, such as a later EmbeddingGemma version, never changes what an installed app downloads.
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. The LiteRT community (Google AI Edge) converted it to LiteRT. This repository is not affiliated with or endorsed by Google.
- Downloads last month
- 124
Model tree for tibaf/embeddinggemma
Base model
google/embeddinggemma-300m