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memvid-embedding-models
sungo-ganpare/memvid-embedding-models
memvid-embedding-models is a machine learning model from sungo-ganpare. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for none.
Packaged ONNX embedding models for the Japanese-enabled memvid fork.
Access
Public
Updated Apr 5, 2026
Repo size
3.6 GB
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0
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Repo makeup
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.onnx_data2.2 GB · 62%
At a glance
- Library
- none
- Access
- Public
- Created
- Apr 5, 2026
- Updated
- Apr 5, 2026
- SHA
- dfa2891f
Model card
From the Hugging Face model README
memvid-embedding-models
Packaged ONNX embedding models for the Japanese-enabled memvid fork.
GitHub repository:
This model repo is used by the setup scripts in the GitHub repo:
scripts/setup_japanese_models.ps1scripts/setup_japanese_models.sh
Included models
multilingual-e5-large
Files:
multilingual-e5-large/multilingual-e5-large.onnxmultilingual-e5-large/model.onnx_datamultilingual-e5-large/multilingual-e5-large_tokenizer.json
Original model:
intfloat/multilingual-e5-large
License:
- MIT
ruri-pt-large
Files:
ruri-pt-large/ruri-pt-large.onnxruri-pt-large/vocab.txtruri-pt-large/tokenizer_config.jsonruri-pt-large/special_tokens_map.json
Original model:
cl-nagoya/ruri-pt-large
License:
- Apache-2.0
Usage
Windows:
powershell -ExecutionPolicy Bypass -File .\scripts\setup_japanese_models.ps1
Linux / macOS:
bash ./scripts/setup_japanese_models.sh
See the GitHub repo for memvid integration details and the current tokenizer fallback notes.
- Library
- none
- Created
- Apr 5, 2026
- Updated
- Apr 5, 2026