Support benchmark using prebuilt artifacts
@huydhn arbeitet bereits daran.
Seit 06.2.2025.
- Vorherrschende Sprache
- Python
- Sterne
- 5k
- Forks
- 1.2k
- Ø Merge
- 2 T. 10 Std.
- Gemergte PRs (30 T.)
- 581
Beschreibung
🚀 The feature, motivation and pitch
Enable this for on-demand workflow only, to offer developers additional flexibility and efficiency.
Scenarios where benchmarking w/ prebuilt artifacts are needed:
- Sometimes the pte model may come from outside, for example the model may come from external partners. Or the model is downloaded from the executorch community from Hugging Face, https://huggingface.co/executorch-community/DeepSeek-R1-Distill-Llama-8B/tree/main.
- Developers who work on the runtime may not necessarily to re-export the same model all the time.
- Developers who work on exporting may not need to build the banchmark app all the time
UX:
- via GitHub UI
- via script
Source of the artifacts to be used in the benchmark workflow:
- pte models from Hugging Face, e.g. https://huggingface.co/executorch-community/Llama-3.2-1B-Instruct-ET/tree/main
- From S3 (uploaded by developers/users)
We will need to define the UX to support this feature. For example, allow users to upload prebuilt artifacts via script. The script will return with links to the artifacts. Then users can schedule an on-demand workflow via UI, or users can do everything via the script.
Policy and TTL to keep the uploaded artifacts.
CC: @digantdesai @kimishpatel @cccclai
Alternatives
No response
Additional context
No response
RFC (Optional)
No response
cc @huydhn @kirklandsign @shoumikhin @mergennachin @byjlw
Beitragsleitfaden
Erste Schritte
- Lies das ganze Issue und danach den Beitragsleitfaden des Projekts.
- Schreib ins Issue, dass du es übernimmst — das erspart doppelte Arbeit.
- Forke das Repository und arbeite in einem Branch.
- Öffne einen Pull Request, der die Issue-Nummer nennt.
Bewertung
Dieses Issue wurde noch nicht bewertet.