pytorch/serve

add support for SeTFiT models

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#2,107 opened on Feb 5, 2023

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good first issuetriaged

Description

馃殌 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

Contributor guide

Tech stack
pythonpytorchjava
Domain
backendmachine learning
Issue type
feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
3
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
1-2 days
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
stale
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
mostly clear
Prerequisites
familiarity with SetFitPyTorch Serve basicsPython package management
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
40
Research direction
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.
add support for SeTFiT models 路 pytorch/serve#2107 | Good First Issue