Results for “strangler-fig-pattern”

Configure fault tolerance, straggler detection, preemption, in-process restart, and re-run state machine for Megatron Bridge training jobs.

Generates structured VGL JSON for Bria FIBO models, giving deterministic control over objects, lighting, camera, composition, and style instead of natural language prompts.

Craft Higgsfield-grade, hyper-structured image-generation prompts for every blog visual. MANDATORY before any image generation call (generate-visuals, Replicate, GPT-Image, Nano Banana). A weak one-line prompt is a gate failure — every [VISUAL] placeholder gets a full structured prompt built with this skill first.

Flamingo: A Visual Language Model for Few-Shot Learning

Generate images with Flux 2 Klein (Black Forest Labs' distilled fast variant of Flux 2) on RunComfy — bundled with the model's documented prompting patterns so the skill gets sharper output than naive prompting against the same model. Documents Flux 2 Klein's strengths (sub-second latency, multi-reference brand styling, declarative subject-first prompts), the step-count strategy (4–8 for fast iteration, ~25 for polish), the 9B vs 4B variant trade-off, and when to route to Flux 2 Pro / Seedream 5 / GPT Image 2 instead. Calls `runcomfy run blackforestlabs/flux-2-klein/9b/text-to-image` (or `/4b/`) through the local RunComfy CLI. Triggers on "flux 2 klein", "flux-2-klein", "flux klein", "BFL flux 2", or any explicit ask to generate with this model.

Generates structured VGL JSON prompts for Bria's FIBO image generation models, covering text-to-image, editing, inpainting, outpainting, and captioning with a deterministic schema.

Generates game-ready sprite bundles from a text description, including character animations, 8-direction sprite sets, and exports to sprite sheets, manifest.json, Aseprite JSON, GIF/APNG, and individual PNG frames.

Adds a persistent pattern or rule that Ralph will remember and apply to future stories.

Generate images from text prompts, perform image-to-image translation, inpainting, and build custom diffusion pipelines using Stable Diffusion models via HuggingFace Diffusers.

Simplest distributed training API. 4 lines to add distributed support to any PyTorch script. Unified API for DeepSpeed/FSDP/Megatron/DDP. Automatic device placement, mixed precision (FP16/BF16/FP8). Interactive config, single launch command. HuggingFace ecosystem standard.