OptimalScale / OptimalScale/LMFlow
Experiments for speculative_decoding
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- Python
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Description
"We tested the speculative inference using the first 100 inputs from alpaca test dataset as prompts. When model=gpt2-xl, draft_model=gpt2".
I want to test speedup for my own model and draft_model. Where can I found the scripts for this?
Thank you in advance.
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 searching the repository for speculative_decoding, gpt2-xl, and draft_model, using the experiment described with the first 100 Alpaca test inputs as the reference. Done means identifying or documenting the scripts needed to measure speedup with a user's own model and draft model.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning
- Issue type
- Documentation
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100