https://github.com/vdaas/vald-demo
https://github.com/vdaas/vald-demo
Last synced: about 1 month ago
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- Host: GitHub
- URL: https://github.com/vdaas/vald-demo
- Owner: vdaas
- License: apache-2.0
- Created: 2021-04-20T06:38:26.000Z (about 4 years ago)
- Default Branch: main
- Last Pushed: 2024-01-23T00:36:12.000Z (over 1 year ago)
- Last Synced: 2024-01-23T02:59:06.087Z (over 1 year ago)
- Language: Jupyter Notebook
- Size: 5.72 MB
- Stars: 5
- Watchers: 4
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Vald Demo
Vald is a highly scalable, distributed, fast approximate nearest neighbor dense vector search engine.
This repository shows example use cases with standard datasets.
Please follow the example list and try examples.
**NOTE: It is recommended to do ["Get Started"](https://vald.vdaas.org/docs/tutorial/get-started/) before trying examples.**
## Requirement
- Kubernetes: v1.24~
- Helm: v3~
- Docker: v20~
Each tutorial has individual requirements, so please refer to each document for details.
## Example Contents
| Name | Use case | Data Category | Dimension | Distance Type |
| :------------------- | :---------------- | :------------ | --------: | :------------ |
| [chiVe(ja)](./chive) | Similarity Search | Text | 300 | Cosine |