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mlops
20 postsnebius-actions: Fine-Tune and Deploy LLMs via GitHub Actions on Nebius
nebius-actions is a GitHub Actions toolkit for fine-tuning and deploying LLMs end-to-end on Nebius GPU infrastructure using Axolotl and vLLM.
PromptLedger v0.7 adds CI regression gates for prompt evaluation
PromptLedger v0.7 adds evaluation runs, metric comparisons, and policy-based regression gates for CI-safe prompt releases.
From a 48-hour PDF rabbit hole to a repeatable research pipeline
An engineer's 48-hour struggle extracting data from academic PDFs led to an automated, auditable research pipeline with measurable gains in speed and reliability.
CommitBrief — AI code reviews, right in your terminal
A provider-agnostic, local-first CLI that reviews your staged changes, a historic range, or a whole GitHub pull request. Zero telemetry, no server. Free and open source.
commitbrief.comLangGraph Pipelines Can Succeed and Still Be Wrong
LangGraph pipelines can finish cleanly while routing decisions silently drift wrong. See why maker/checker divergence and state snapshots catch what standard monitoring misses.
Multimodal Models Fail at Sampling, Not Understanding
Multimodal models aren't bottlenecked by capability but by sampling defaults—frame rate, chunking, cropping—that silently limit what they perceive.
A 5-Layer AI Quality Architecture for 5 Production AI Systems
An engineer details a 5-layer quality architecture built across 5 production AI systems like ARIA, using input, processing and output gates to catch hallucination and drift.
Why LLM-as-judge scores flip between identical runs
An LLM judge gate flipped between 0.79 and 0.82 on identical inputs. Sampling temperature, model drift and vague rubrics cause the jitter; k-sampling and a noise band fix it.
AI's Next Frontier Is Infrastructure Control, Not Models
Mozilla's Otari project argues enterprise AI's real bottleneck isn't model quality but cost visibility, multi-provider sprawl, and governance at scale.
Trendyol Speeds Up Search Ranking Model Deployment
Trendyol built a config-driven ranking platform that turns a multi-day Go deployment process into a single YAML file, cutting model lead time dramatically.
Decoupling Prompt Engineering from Your Deployment Pipeline
Explore ways to decouple prompt engineering from your deployment processes. Enhance your development cycle with the Humanloop MCP server.