Milvus Model Lib
The milvus-model library provides the integration with common embedding and reranker models for Milvus, a high performance open-source vector database built for AI applications. milvus-model lib is included as a dependency in pymilvus, the Python SDK of Milvus.
milvus-model supports embedding and reranker models from service providers like OpenAI, Voyage AI, Cohere, and open-source models through SentenceTransformers or Hugging Face Text Embeddings Inference (TEI) .
milvus-model supports Python 3.8 and above.
Installation
If you use pymilvus, you can install milvus-model through its alias pymilvus[model]:
pip install pymilvus[model]
# or pip install "pymilvus[model]" for zsh.
You can also install it directly:
pip install pymilvus.model
To upgrade milvus-model to the latest version, use:
pip install pymilvus.model --upgrade
If milvus-model was initially installed as part of the PyMilvus optional components, you should also upgrade PyMilvus to ensure compatibility. This can be done with:
pip install pymilvus[model] --upgrade
If you need to install a specific version of milvus-model, specify the version number:
pip install pymilvus.model==0.3.0
This command installs version 0.3.0 of milvus-model.
Release files for pymilvus.model 0.3.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pymilvus_model-0.3.3.tar.gz | 36.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pymilvus_model-0.3.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 84.2 kB
Release files / pymilvus_model-0.3.3.tar.gz
| Download URL | pymilvus_model-0.3.3.tar.gz |
|---|---|
| Size | 36.5 kB |
| Tags | Source |
|
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No |
| Uploaded via |
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Release files / pymilvus_model-0.3.3-py3-none-any.whl
| Download URL | pymilvus_model-0.3.3-py3-none-any.whl |
|---|---|
| Size | 47.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
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