MaartenGr / MaartenGr/BERTopic
Converting GPU model to CPU for inference
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- Dominant language
- Python
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Description
I am training a model with the GPU versions of UMAP and HDBSCAN for better performance. Once finished I would like to use the model to perform daily inference on new data. Is it possible to convert the GPU UMAP and HDBSCAN model to CPU variants, so that I am not required to use the GPU for inference?
Thanks?
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The issue names GPU UMAP and HDBSCAN models used for training and daily CPU inference, but it identifies no files, tests, or entry points. Start by locating the relevant BERTopic integration and determine whether a CPU inference workflow can be demonstrated; done would require a clear, reproducible answer.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100