catalog / layers

NanoChat.NET — engine layer

The .NET port's engine capabilities, as reachable from code.

16 capabilities 7 sections extracted from Engine capabilities (Dpp.Nano) source: D:\Dev\Lab\NanoChat.NET

Build against it

# give your agent the catalog — no account, no install
claude mcp add provespec -- npx -y provespec-mcp

# then, from any agent session
spec_get(slug: "nanochat-net-engine")                → the capability tree
spec_checklist(slug: "nanochat-net-engine")          → the questions to answer
spec_grade(slug: "nanochat-net-engine", grades: [...])  → parity % + the gap list

# or just fetch it
curl https://provespec.com/catalog/nanochat-net-engine/spec.json

Grade every capability below as yes · partial · no · na, with a file reference as evidence. Whatever you leave ungraded counts as missing — the gap list is the work queue.

Or just paste this to your agent

Use the ProveSpec MCP server. Fetch the "nanochat-net-engine" spec with
spec_get, then walk spec_checklist and grade this repository against it —
one verdict per capability, each with a file reference as the note.
Call spec_grade with the results and give me the gap list as the plan.

If the server is not registered, add it first:
  claude mcp add provespec -- npx -y provespec-mcp

The specification

Tokenizer 2

  • Train tokenizer BpeTokenizer training + tokenizer-train CLI
  • Inspect vocabulary & merges BpeTokenizer surfaces ranks/merges

Data 1

  • Register & inspect corpora LocalFileCatalog, TextJsonlInspector

Training 4

  • Pretraining runs Trainer + EngineService, 8 pipeline stages
  • Task/SFT training (5 kinds) TaskDataPipeline + objectives
  • Resume from checkpoint TrainingCheckpointStore + signatures
  • RL training loop GrpoRollout + RlTrainingLoop / rl-train

Evaluation 3

  • BPB / CORE / GSM8K / ARC / MMLU evaluation layer + integrity gates
  • Evaluation history & drilldown data EvaluationHistory, EvaluationTrace
  • Inference performance benchmark InferenceBenchmark roofline

Inference 2

  • Chat sessions (streamed, tool-use) ChatSession, InferenceEngine, ToolUseStateMachine
  • Task runtime (generate/classify/rank/embed) NanoRuntime + TaskRuntimeClient

Checkpoints & models 3

  • Checkpoint inventory CheckpointInventory lineage/tag/step
  • Registry: deploy & rollback ModelRegistry per task kind
  • Upstream checkpoint import UpstreamCheckpointImporter

Internals 1

  • GPU/tensor/kernel state TensorTracker, NanoKernel, kernel self-test
Download spec.json All 53 specs