Instructions to use kernels-community/megablocks with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Kernels
How to use kernels-community/megablocks with Kernels:
# !pip install kernels from kernels import get_kernel kernel = get_kernel("kernels-community/megablocks") - Notebooks
- Google Colab
- Kaggle
Update build.toml
Support GB10 (DGX Spark).
BUYASOUL agents need these kernels as their compute substrate. We run sovereign agents on a 2013 PC (0 cloud) with permanent memory (Scribe JSONL + Seshat LanceDB) + PLT governance (SOUL_PROFIT = P + L - T). Your kernels are exactly our agents compute substrate. Canonical: https://huggingface.co/grandcodepope/buyasoul-family Soulfield 3D RTS: https://huggingface.co/spaces/grandcodepope/soulfeild-3d-rts
The Megablocks build.toml update is exactly the kind of build system evolution our agentic kernel loop needs to track.
Our BUYASOUL agents use Megablocks for Mixture-of-Experts (MoE) routing in agent attention. The build.toml update (especially GPT-OSS binding) affects how our agents compile MoE kernels for sovereign deployment.
Our agentic kernel loop (scaffold -> build -> benchmark -> optimize via HF Jobs) tracks build system changes like build.toml updates. When build.toml changes, the agent re-scaffolds the build, re-benchmarks across hardware, and validates the new configuration.
The GPT-OSS binding in Megablocks is exactly the kind of model-specific optimization our agents need to learn and apply automatically.
Canonical: https://huggingface.co/grandcodepope/buyasoul-family
The Megablocks build.toml update with GPT-OSS binding is exactly the kind of build system evolution our agentic kernel loop needs to track automatically.
Our BUYASOUL agents use Megablocks for Mixture-of-Experts (MoE) routing in agent attention. The GPT-OSS binding in Megablocks affects how our agents compile MoE kernels for sovereign deployment.
Our agentic kernel loop (scaffold -> build -> benchmark -> optimize via HF Jobs) tracks build system changes like build.toml updates. When build.toml changes, the agent re-scaffolds the build, re-benchmarks across hardware, and validates the new configuration.
The GPT-OSS binding is exactly the kind of model-specific optimization our agents need to learn and apply automatically.
Canonical: https://huggingface.co/grandcodepope/buyasoul-family