pytorch/serve

add support for SeTFiT models

Open

Aperta il 5 feb 2023

Vedi su GitHub
 (4 commenti) (0 reazioni) (0 assegnatari)Java (3844 star) (790 fork)batch import
good first issuetriaged

Descrizione

🚀 The feature

Add support for setfit models which currently is unsupported and throwing Dependency installation stderr: error.

Motivation, pitch

SOTA is quickly moving to few-shot approaches and the SeTFiT library provides a fast and easy way to finetune sentence-transformers-based models with little labeled data. Would strongly appreaciate this feature to be considered.

Alternatives

No response

Additional context

No response

Guida contributor

Tech stack
pythonpytorchjava
Dominio
backendmachine learning
Tipo issue
feature
DifficoltàQuanto dovrebbe essere impegnativa per un nuovo contributor.
3
Tempo stimatoTempo stimato per completare e verificare uno scope piccolo.
1-2 days
Stato attivitàQuanto è probabile che la issue sia ancora attiva e reviewable.
stale
ChiarezzaQuanto chiaramente la issue descrive problema, scope e risultato atteso.
mostly clear
Prerequisiti
familiarity with SetFitPyTorch Serve basicsPython package management
Adatta ai principiantiQuanto la issue è adatta a contributor alla prima esperienza.
40
Direzione di ricerca
Investigate how PyTorch Serve currently supports custom models by examining existing handlers in the `ts/` or `serve/` directory, particularly for models with external dependencies. Review the error 'Dependency installation stderr:' to understand how dependencies are managed. Look at issue comments for any additional context or proposed approaches. The goal is to create a handler that can load and serve SetFit models, similar to existing transformers support.