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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. | |