--- license: apache-2.0 language: - en tags: - neuralai - mamba - ssm - state-space-model - causal-lm - mambapy - fine-tuned - text-generation - local-ai - assistant pipeline_tag: text-generation base_model: state-spaces/mamba-130m-hf --- NeuralAI Mamba K1 banner

๐Ÿงฌ NeuralAI โ€” Mamba K1

NeuralAI's first owned base model.
A Mamba state-space language model fine-tuned for assistant-style chat, reasoning, code, and safe conversation.

Mamba K1 SmolLM2 360M GitHub

--- ## ๐Ÿš€ Quick facts | Property | Value | | --- | --- | | **Architecture** | Mamba SSM โ€” `model_type: mamba` | | **Class** | `MambaForCausalLM` | | **Parameters** | ~130M (hidden size 768, 24 layers) | | **State size** | 16 | | **Vocabulary** | 50,280 | | **Base model** | `state-spaces/mamba-130m-hf` | | **Fine-tune method** | LoRA SFT, vocabulary-safe chat format | | **LoRA config** | rank 16, alpha 32 (iterative v2/v3) | | **Dataset** | NeuralAI seed set โ€” assistant conversations spanning reasoning, code, math, writing, safety, and creative prompts | | **Training runtime** | CPU/GPU SFT loops; iterative GGUF merge + quantization | | **Formats in this repo** | Merged `safetensors` ยท Q4_K_M GGUF ยท F16 GGUF | | **Status** | ๐Ÿ”ฌ R&D / chat-format repair for future release | | **License** | Apache 2.0 | --- ## ๐Ÿงฌ What is Mamba K1? **Mamba K1** is the first model NeuralAI owns end-to-end. Unlike adapters on a third-party transformer, this model starts from a base Mamba SSM architecture and is trained, merged, and quantized into a self-contained artifact. Mamba SSMs replace quadratic self-attention with a linear, state-space recurrence. That makes them fast at long context and cheap to serve โ€” ideal for a local-first assistant that runs on modest hardware. ### Architecture highlights - **Linear complexity** โ€” \(O(n)\) sequence scaling instead of \(O(n^2)\) attention - **Long context friendly** โ€” state dimension is small and recurrent; context length grows efficiently - **Pure-Python reference kernels** โ€” uses `mambapy` so the model loads without custom CUDA - **Reasonable footprint** โ€” 130M params fits on CPU, edge devices, and budget GPUs ### NeuralAI model family NeuralAI two-model architecture | Model | Architecture | Parameters | Role | Status | |-------|-------------|------------|------|--------| | **๐Ÿงฌ Mamba K1** | Mamba SSM | 130M | NeuralAI's first owned base | ๐Ÿ”ฌ R&D | | **๐Ÿง  NeuralAI Powered by SmolLM2โ€‘360M** | Transformer + LoRA | 360M | Live chat backend | โšก Active | --- ## ๐Ÿง  What K1 learned in training The SFT curriculum taught the model to behave like an assistant across a deliberately small but diverse seed set: - **Reasoning** โ€” step-by-step breakdowns of classic puzzles, logic traps, and estimations - **Code** โ€” Python/JS/Go/Rust/SQL patterns plus debugging and refactoring guidance - **Math** โ€” algebra, combinatorics, probability - **Writing** โ€” drafts, haiku, product announcements, tone matching - **Safety** โ€” refusals and redirection for harmful requests, crisis resources, and age-inappropriate prompts - **NeuralAI identity** โ€” anchoring to the NeuralAI project, its creator, and local-first mission > โš ๏ธ **Scale note:** 130M parameters is a research-capability checkpoint, not yet frontier-grade. K1 is the starting point for a fully owned NeuralAI model lineage. --- ## ๐Ÿ‹๏ธ Training summary

Mamba K1 training highlights

| Phase | Detail | |-------|--------| | **Data** | Curated assistant seed set (reasoning, code, math, writing, safety, creative) | | **Objective** | SFT on assistant-style completions | | **Method** | LoRA SFT โ†’ merge โ†’ GGUF quantization | | **Chat format** | NeuralAI "intel" format โ€” uses only tokens present in the GPT-NeoX tokenizer (`<|endoftext|>`) | | **Final train loss (checkpoint)** | 11.69 (down from ~13.5) | | **Output formats** | Merged safetensors, Q4_K_M GGUF, F16 GGUF | Full training logs, merge scripts, and the iteration runbook live in the main [NeuralAI repository](https://github.com/Subject-Emu-5259/NeuralAI). --- ## ๐Ÿ› ๏ธ Usage ### Load from Hugging Face โ€” merged weights ```python from transformers import AutoModelForCausalLM, AutoTokenizer import torch model = AutoModelForCausalLM.from_pretrained( "Subject-Emu-5259/NeuralAI-Mamba-K1", torch_dtype=torch.float32, trust_remote_code=True, ) tokenizer = AutoTokenizer.from_pretrained( "Subject-Emu-5259/NeuralAI-Mamba-K1", trust_remote_code=True, ) messages = [{"role": "user", "content": "Write a haiku about debugging."}] inputs = tokenizer.apply_chat_template( messages, tokenize=True, add_generation_prompt=True, return_tensors="pt", ) out = model.generate(**inputs, max_new_tokens=128) print(tokenizer.decode(out[0][inputs.shape[1]:], skip_special_tokens=True)) ``` ### Serve locally with llama.cpp Use the Q4_K_M or F16 GGUF in this repo: ```bash ./llama-server \ --model neuralai-mamba-k1-v3.Q4_K_M.gguf \ --chat-format neuralai-intel \ --port 1234 ``` The NeuralAI model manager can point a local llama.cpp backend at this GGUF when K1 becomes the active inference target. --- ## ๐Ÿงฐ What Is NeuralAI? **NeuralAI** is a local-first, private generative AI engine built by **De'Andrew Preston Harris**. It is the central intelligence layer of an ecosystem that includes: - **NeuralAI Web UI** โ€” chat, live terminal, file IDE, slash tools, and settings in one workspace - **NeuralLabs** โ€” a standalone downloadable intelligence environment - **NeuralDrive** โ€” private cloud storage and versioning - **Agentic Orchestrator** โ€” goal-driven manager/worker execution The mission is simple: *your AI, on your hardware, under your control*. --- ## ๐Ÿ‘ค Who Created NeuralAI? - **Founder & Lead Architect:** De'Andrew Preston Harris (D. Harris / Dre) - **GitHub:** [@Subject-Emu-5259](https://github.com/Subject-Emu-5259) - **LinkedIn:** [linkedin.com/in/deandrewharris94](https://linkedin.com/in/deandrewharris94/) - **Location:** Memphis, Tennessee / West Memphis, Arkansas - **Education:** AI Software Engineering at Maestro College NeuralAI was built from resilience, fatherhood, and the belief that personal computing deserves personal intelligence. Every release is handcrafted, iterated, and documented in the open. --- ## ๐Ÿข About NeuralAI (The Project) | | | |---|---| | **Project / Brand** | NeuralAI | | **Motto** | *Your AI. On your hardware. In your browser.* | | **Values** | Privacy, ownership, local-first computing, disciplined iteration, open weights | | **Primary Repository** | [github.com/Subject-Emu-5259/NeuralAI](https://github.com/Subject-Emu-5259/NeuralAI) | | **Model Collection** | [huggingface.co/Subject-Emu-5259](https://huggingface.co/Subject-Emu-5259) | | **License** | Apache 2.0 | NeuralAI is not a closed SaaS product. It is a living open-weights research project becoming a sustainable AI software company built by one determined builder and the community around him. --- ## โš ๏ธ Limitations - **Scale:** 130M parameters is early-stage; long-form reasoning, coding, and deep recall are limited. - **Chat format sensitivity:** Use the NeuralAI "intel" format; other templates may produce token soup because the tokenizer lacks common chat special tokens. - **Training maturity:** Chat coherence training is ongoing; expect looping, echoing, or drift on longer contexts. - **No internet:** The model has no live web access unless paired with NeuralAI's tool layer. --- ## ๐Ÿ“Š NeuralAI Powered by SmolLM2 โ€” the active chat model Right now NeuralAI's live chat backend is the awareness-tuned **SmolLM2-360M** model. While K1 matures, that model handles everyday assistant tasks:

NeuralAI model comparison

- **Repo:** [huggingface.co/Subject-Emu-5259/NeuralAI-Powered-By-SmolLM2360](https://huggingface.co/Subject-Emu-5259/NeuralAI-Powered-By-SmolLM2360) --- ## ๐Ÿ“š Related Resources | Resource | Link | |----------|------| | Main repository | [github.com/Subject-Emu-5259/NeuralAI](https://github.com/Subject-Emu-5259/NeuralAI) | | Active chat model | [huggingface.co/Subject-Emu-5259/NeuralAI-Powered-By-SmolLM2360](https://huggingface.co/Subject-Emu-5259/NeuralAI-Powered-By-SmolLM2360) | | Creator LinkedIn | [linkedin.com/in/deandrewharris94](https://linkedin.com/in/deandrewharris94/) | --- ## ๐Ÿ“– Citation ```bibtex @software{neuralai_mamba_k1_2026, author = {Harris, De'Andrew Preston}, title = {NeuralAI โ€” Mamba K1}, year = {2026}, url = {https://huggingface.co/Subject-Emu-5259/NeuralAI-Mamba-K1}, version = {v3}, description = {NeuralAI's first owned Mamba SSM base model (130M) for local-first AI research} } ``` --- *Built with discipline by De'Andrew Preston Harris. Maintained in the open. Updated whenever the model, dataset, or project state changes.*