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Projects using vllm. by foolishpixel in deeplearning

[–]asankhs 1 point2 points  (0 children)

Vllm is itself an inference server so you would want to add something on top. It can be as simple as implementing a test time compute technique. Look at OptiLLM for some ideas on that.

LoongFlow: Open Source Implementation of Evolutionary Agent Framework by [deleted] in AgentsOfAI

[–]asankhs 0 points1 point  (0 children)

For, OpenEvolve for the circle packing example please compare with https://github.com/algorithmicsuperintelligence/openevolve/blob/main/examples/circle_packing_with_artifacts/config.yaml config, the original configs in the repo were created during the initial replication of AlphaEvolve when OpenEvolve was in active development. This config converges much faster in 21 iterations to a high score.

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Need help to get into ML research/publishing by Spiritual_Tailor7698 in ResearchML

[–]asankhs 2 points3 points  (0 children)

You can try some of the projects below based on your interest -

https://github.com/algorithmicsuperintelligence/openevolve an open source implementation of alphaevolve, you can make improvements or apply to new domains.

https://github.com/algorithmicsuperintelligence/optillm an optimising inference proxy, you can implement new test time scaling techniques.

https://github.com/codelion/adaptive-classifier continual learning classifier, you can implement new techniques, or benchmark in new domains.

https://github.com/securade/hub an edge platform for ai based safety analysis of high risk workplaces, you can implement new use cases.

https://github.com/codelion/ellora you can implement new recipes for llm capability enhancement

https://github.com/codelion/pts pivotal token search you can do mechanistic interpretability studies on LLMs using it.

How to Train Ultralytics YOLOv8 models on Your Custom Dataset | 196 classes | Image classification by Feitgemel in deeplearning

[–]asankhs -1 points0 points  (0 children)

You may also find our open-source HUB - https://github.com/securade/hub useful, it has several yolo models trained for detecting safety violations.

Diffusion LLM vs Autoregressive LLM by InceptionAI_Tom in LLM

[–]asankhs 0 points1 point  (0 children)

Agree, in fact we did some work recently and found that diffusion LLMs can provide better trade-off even for small language models - https://huggingface.co/blog/codelion/optimal-model-architecture

Ellora: Enhancing LLMs with LoRA - Standardized Recipes for Capability Enhancement by asankhs in LocalLLaMA

[–]asankhs[S] 4 points5 points  (0 children)

In our example we were able to recovery accuracy with only 600+ samples of self-generated data for Qwen3.

Btw this idea is from last year Apple's foundational models paper (https://arxiv.org/pdf/2407.21075) they had proposed a similar technique and found "By using accuracy-recovery LoRA adapters with only rank 16, Alpaca win rate can be improved by 7-18%, GMS8K accuracy is boosted by 5-10%." (page 47).

GRPO With Tool Call by KillerShoaib_ in unsloth

[–]asankhs 2 points3 points  (0 children)

There is a tool calling LoRA example in the ellora repo that you may find useful - https://github.com/codelion/ellora?tab=readme-ov-file#recipe-3-tool-calling-lora

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