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n-orca v0.1.0

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@jascal jascal released this 23 May 18:59
v0.1.0
ba7f58b

n-orca v0.1.0 — initial release

A Markdown DSL for declaring, verifying, visualizing, and executing neural network architectures. Sibling to orca-lang (state machines) and q-orca-lang (quantum circuits).

Install

pip install n-orca                # core
pip install "n-orca[torch]"       # + PyTorch (compile to runnable nn.Module)
pip install "n-orca[hf]"          # + huggingface_hub
pip install "n-orca[mcp]"         # + MCP server for Claude Code
pip install "n-orca[all]"         # everything

What's in 0.1.0

Language + tooling

  • Parser, 5-stage verifier (naming → structural → shape → resource → op), ~30-op standard library
  • Compilers to Mermaid flowchart TD and runnable PyTorch nn.Module
  • Round-trip emit→parse→verify is exact

Hugging Face integration

  • n-orca hf {search,info,download,convert} CLI surface
  • Adapters for GPT-2, LLaMA family (LLaMA / Mistral / Qwen / Gemma / Phi), BERT family (BERT / RoBERTa / DistilBERT / Electra / ALBERT), and ESM-2
  • Reads config.json only — no model code is executed, no trust_remote_code

Sparse autoencoders

  • n_orca.sae.{topk_sae, l1_sae, jumprelu_sae} programmatic builders
  • New ops: TopK(k) and JumpReLU(d, theta_init)

Non-LLM world models (econ-sae substrates)

  • n_orca.world_models.{world_model, deep_world_model, attn_world_model}

MCP server

  • 10 tools: list_architectures, hf_search, hf_info, convert_from_hf, verify_markdown, compile_mermaid, compile_pytorch, render_markdown, build_sae, build_world_model
  • claude mcp add n-orca <python> -m n_orca.mcp_server

Test status

111 tests passing on Python 3.10 / 3.11 / 3.12 (parser, verifier, ops, builders, Mermaid + PyTorch compilers, CLI, MCP stdio protocol, end-to-end forward passes).

What's not in 0.1.0

  • Whisper-style encoder-decoder topologies
  • Mixture-of-experts FFN
  • Optional --collapse-repeat rendering for very deep architectures (LLaMA-7B / BERT renders are correct but one tall column)
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