Comments (3)
This is what people use for deploying LLMs on babel (prev tir). https://github.com/ProKil/lti-llm-deployment
Known problems:
- Not batching requests. So the speed is very, very slow.
- The default client is not using
aiohttp
(non-blocking), but usingrequests
(blocking)
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I am trying to use vllm as an alternative backend. It supports an OpenAI-like API.
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Done at the sotopia side.
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Related Issues (20)
- [BUG]: Fix and replace the uncleaned "Agent1" and "Agent2" appeared in the scenario and social goal
- [FEAT]: Build human evaluation pipeline HOT 1
- [BUG]: Data Directory deleted from /llm_ft
- [FEAT]: Create new scenarios based on new inspirational prompts
- [FEAT]: Implement Automated Self-Training Pipeline HOT 1
- [FEAT]: Self-Train Pipeline Backbone
- [FEAT]: Intermediate saves of checkpoints in sft trainer
- [FEAT]: Automated uploading to gcp storage
- [FEAT]: Self-Train Pipeline on Babel HOT 1
- [FEAT]: adding gcloud utils for upload, download, and check metadata
- [FEAT]: Training Pipeline with Improve Steps
- [FEAT]: Modularize codebase for self-training
- [FEAT]: Save full model during training
- [FEAT]: Changes to custom callbacks to accomodate fastchat deploy
- [FEAT]: Add Monitor to Eval Step Results HOT 1
- [FEAT]: Launch a human evaluation report based on Prolific HOT 2
- [FEAT]: Add interactive demo
- [FEAT]: Add jupyter notebook demo HOT 2
- [BUG]: Behavior cloning can not be reproduced
- [BUG]: Questions about the size of the dataset.
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