Loading model on low CPU memory
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enhancement
- Dominant language
- C++
- Stars
- 4.7k
- Forks
- 536
- Avg merge
- 12h 12m
- Merged PRs (30d)
- 4
Description
I am struggling to load a quantized model lacking sufficient CPU memory to load the weights.
Usually I would split the weights up in multiple shards and then load them accordingly.
Is this, or something similar, also possible in CTranslate?
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
Start by examining CTranslate2's model-loading path and how quantized model weights are currently handled. The issue does not name files or tests, so first map the relevant loading code and existing memory behavior. Done means establishing whether sharded weight loading, or a comparable low-CPU-memory approach, is supported.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- cpp
- Domain
- machine-learning, performance
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 25/100