Philipp Schmid
Technical Lead & Open-Source LLM Specialist | Ex-Technical Lead at Hugging Face
Verified Proof of Work Artifacts
2 items catalogedEach artifact below represents an authenticated research publication, production code repository, or technical architectural framework directly authored or co-created by Philipp Schmid. Every entry undergoes editorial source verification.
Serverless LLM Inference Optimization & TGI Deployment Blueprint
An end-to-end production deployment playbook detailing continuous batching, PagedAttention integration, and tensor parallelism configurations using Text Generation Inference (TGI) on cloud infrastructures.
Production throughput benchmarks rely on dedicated cloud GPU clusters (NVIDIA A10G/A100); cold start latency must be managed in serverless scaling.
Production Open-Source LLM Fine-Tuning & Evaluation Cookbook with TRL and vLLM
Comprehensive production blueprint demonstrating automated DPO, SFT, and vLLM deployment pipelines with continuous evaluation harnesses on AWS SageMaker and Kubernetes.
Requires careful GPU memory budget tuning when scaling multi-GPU distributed tensor parallelism across heterogenous cluster nodes.