dashVectorSpace / COLAB_INSTRUCTIONS.md
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Deploy 9-Row Benchmark (via API)
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# Running dashVectorspace on Google Colab
Since the ingestion process can be compute-intensive, running on Google Colab (especially with a GPU) is a great option.
## Steps
3. **Setup Environment**:
Open the notebook `notebooks/dashVector_full_benchmark.ipynb`.
Since it clones the code directly from Hugging Face, you do **not** need to upload any zip files.
Simply **Run All Cells**.
The notebook will:
- Clone `https://huggingface.co/spaces/dashVector/dashVectorSpace`
- Install dependencies
- Run the 25k Benchmark
- Prompt to download artifacts
4. **Download Artifacts**:
The notebook will save models to the `models/` directory.
Zip and download this folder to your local machine:
```python
!zip -r models.zip models
from google.colab import files
files.download('models.zip')
```
Then, place these files into `dashVectorspace/models/` and re-deploy.