Welcome to the PyTorch Ecosystem for LLM Fine-tuning Mini Summit
summary
First PyTorch fine tuning mini summit presents a packed agenda with a keynote on the Llama ecosystem, three invited demos from the founders of Axolotl, Unsloth, torchtune, and a final panel that includes authors of bitsandbytes and QLoRA and maintainers of LM evaluation tools. Sessions focus on concrete techniques: memory and quantization benchmarks, parameter efficient recipes, reproducible evaluation protocols, and performance numbers at scale so attendees can compare methods and tools directly.
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04mOpening Remarks
35mCreating Your Own LLM Tuning Platform with Open Source Technologies
53mLLM Quality Optimization Bootcamp
09mTailoring Llama for Your Needs: Fine-Tuning & Evaluation
29mLocal LLM fine-tuning: a practical example
26mVLLM-Helion: SOTA LLM Performance by Advanced Autotuning and Fine-grained Dispatching
25mFine-Tuning Large Language Models With Declarative ML Orchestration
21mStreamline LLM Fine-Tuning on Kubernetes with Kubeflow LLM Trainer