pytorch/serve

add support for SeTFiT models

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#2,107 创建于 2023年2月5日

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 (4 评论) (0 反应) (0 负责人)Java (3,844 star) (790 fork)batch import
good first issuetriaged

描述

🚀 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

贡献者指南

技术栈
pythonpytorchjava
领域
backendmachine learning
议题类型
feature
难度面向新贡献者的预计实现难度，1 表示很小改动，5 表示专家级工作。
3
预计时间有经验贡献者完成调查、实现、测试并准备 pull request 的粗略时间范围。
1-2 days
活动状态议题当前的可参与程度：新鲜、活跃、陈旧、阻塞或等待维护者输入。
stale
清晰度议题是否清楚说明期望改动、验收标准和下一步。
mostly clear
前置要求
familiarity with SetFitPyTorch Serve basicsPython package management
新手友好度1-100 的估计分数，表示该议题对首次贡献者的友好程度。
40
研究方向
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.