Inkling

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Inkling is a multimodal Mixture-of-Experts model from Thinking Machines Lab. It accepts text, image, video, and audio inputs and generates text.

TaskImage-Text-to-Text / Audio-Text-to-Text
ArchitectureInklingForConditionalGeneration
Parameters975B total / 41B active
PrecisionBF16
HF Orgthinkingmachines

Architecture

Inkling uses a 66-layer decoder with hybrid local and global attention. Each sparse feed-forward layer routes a token to 6 of 256 experts and also evaluates 2 shared experts. Images and video use a hierarchical patch encoder, while audio uses discrete dMel tokens.

NeMo AutoModel retains the checkpoint’s fused expert layout and supports pipeline parallelism and expert parallelism for full-parameter fine-tuning.

Example HF Models

ModelHF ID
Inkling BF16thinkingmachines/Inkling

Example Recipes

RecipeDatasetDescription
inkling_medpix.yamlMedPix-VQAFull SFT with PP8 and EP32

The model requires a multi-node launch. Adjust the data, pipeline, and expert-parallel dimensions to the available cluster before running the recipe.

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