Support benchmark using prebuilt artifacts
@huydhn ci sta già lavorando.
Dal 6/2/2025.
- Lingua principale
- Python
- Stelle
- 5k
- Fork
- 1.2k
- Merge medio
- 2g 10h
- PR unite (30g)
- 581
Descrizione
🚀 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
Guida per i contributori
Apri la guida per i contributori
Come iniziare
- Leggi tutta la issue e poi la guida ai contributi del progetto.
- Commenta sulla issue per dire che te ne occupi tu — evita che due persone facciano lo stesso lavoro.
- Fai un fork del repository e lavora su un branch.
- Apri una pull request che faccia riferimento al numero della issue.
Valutazione
Questa issue non è ancora stata valutata.