README.md

---
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
  Model card maintained by De'Andrew Preston Harris (@Subject-Emu-5259)
  Last synced: 2026-08-13
-->

<img src="neuralai-mamba-k1-banner.png" alt="NeuralAI Mamba K1 banner" width="100%" />

<h1 align="center">🧬 NeuralAI — Mamba K1</h1>

<p align="center">
  <strong>NeuralAI's first owned base model.</strong><br/>
  A Mamba state-space language model fine-tuned for assistant-style chat, reasoning, code, and safe conversation.
</p>

<p align="center">
  <a href="https://huggingface.co/Subject-Emu-5259/NeuralAI-Mamba-K1"><img src="https://img.shields.io/badge/🤗%20Hub-Mamba%20K1-blue" alt="Mamba K1"></a>
  <a href="https://huggingface.co/Subject-Emu-5259/NeuralAI-Powered-By-SmolLM2360"><img src="https://img.shields.io/badge/🤗%20Hub-SmolLM2%20360M-purple" alt="SmolLM2 360M"></a>
  <a href="https://github.com/Subject-Emu-5259/NeuralAI"><img src="https://img.shields.io/badge/GitHub-NeuralAI-181717?logo=github" alt="GitHub"></a>
</p>

---

## 🚀 Quick facts

| Property | Value |
| --- | --- |
| **Architecture** | Mamba SSM — `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 — 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` · Q4_K_M GGUF · F16 GGUF |
| **Status** | 🔬 R&D / chat-format repair for future release |
| **License** | Apache 2.0 |

---

## 🧬 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 — ideal for a local-first assistant that runs on modest hardware.

### Architecture highlights

- **Linear complexity** — \(O(n)\) sequence scaling instead of \(O(n^2)\) attention
- **Long context friendly** — state dimension is small and recurrent; context length grows efficiently
- **Pure-Python reference kernels** — uses `mambapy` so the model loads without custom CUDA
- **Reasonable footprint** — 130M params fits on CPU, edge devices, and budget GPUs

### NeuralAI model family

<img src="neuralai-duo-architecture.png" alt="NeuralAI two-model architecture" width="92%" />

| Model | Architecture | Parameters | Role | Status |
|-------|-------------|------------|------|--------|
| **🧬 Mamba K1** | Mamba SSM | 130M | NeuralAI's first owned base | 🔬 R&D |
| **🧠 NeuralAI Powered by SmolLM2‑360M** | Transformer + LoRA | 360M | Live chat backend | ⚡ Active |

---

## 🧠 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** — step-by-step breakdowns of classic puzzles, logic traps, and estimations
- **Code** — Python/JS/Go/Rust/SQL patterns plus debugging and refactoring guidance
- **Math** — algebra, combinatorics, probability
- **Writing** — drafts, haiku, product announcements, tone matching
- **Safety** — refusals and redirection for harmful requests, crisis resources, and age-inappropriate prompts
- **NeuralAI identity** — anchoring to the NeuralAI project, its creator, and local-first mission

> ⚠️ **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.

---

## 🏋️ Training summary

<p align="center">
  <img src="neuralai-mamba-k1-training.png" alt="Mamba K1 training highlights" width="92%" />
</p>

| Phase | Detail |
|-------|--------|
| **Data** | Curated assistant seed set (reasoning, code, math, writing, safety, creative) |
| **Objective** | SFT on assistant-style completions |
| **Method** | LoRA SFT → merge → GGUF quantization |
| **Chat format** | NeuralAI "intel" format — 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).

---

## 🛠️ Usage

### Load from Hugging Face — 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.

---

## 🧰 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** — chat, live terminal, file IDE, slash tools, and settings in one workspace
- **NeuralLabs** — a standalone downloadable intelligence environment
- **NeuralDrive** — private cloud storage and versioning
- **Agentic Orchestrator** — goal-driven manager/worker execution

The mission is simple: *your AI, on your hardware, under your control*.

---

## 👤 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.

---

## 🏢 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.

---

## ⚠️ 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.

---

## 📊 NeuralAI Powered by SmolLM2 — 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:

<p align="center">
  <img src="neuralai-model-comparison.png" alt="NeuralAI model comparison" width="92%" />
</p>

- **Repo:** [huggingface.co/Subject-Emu-5259/NeuralAI-Powered-By-SmolLM2360](https://huggingface.co/Subject-Emu-5259/NeuralAI-Powered-By-SmolLM2360)

---

## 📚 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/) |

---

## 📖 Citation

```bibtex
@software{neuralai_mamba_k1_2026,
  author       = {Harris, De'Andrew Preston},
  title        = {NeuralAI — 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.*