Text Generation
PyTorch
GGUF
English
quantum
quantum-entropy
from-scratch
char-level
cosmic-synapse-theory
custom-architecture
llama-cpp
continual-learning
reproducible-seed
open-science
null-results
Instructions to use phera-ra/QC67_cosmo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use phera-ra/QC67_cosmo with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf phera-ra/QC67_cosmo # Run inference directly in the terminal: llama cli -hf phera-ra/QC67_cosmo
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf phera-ra/QC67_cosmo # Run inference directly in the terminal: llama cli -hf phera-ra/QC67_cosmo
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf phera-ra/QC67_cosmo # Run inference directly in the terminal: ./llama-cli -hf phera-ra/QC67_cosmo
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf phera-ra/QC67_cosmo # Run inference directly in the terminal: ./build/bin/llama-cli -hf phera-ra/QC67_cosmo
Use Docker
docker model run hf.co/phera-ra/QC67_cosmo
- LM Studio
- Jan
- vLLM
How to use phera-ra/QC67_cosmo with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "phera-ra/QC67_cosmo" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "phera-ra/QC67_cosmo", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/phera-ra/QC67_cosmo
- Ollama
How to use phera-ra/QC67_cosmo with Ollama:
ollama run hf.co/phera-ra/QC67_cosmo
- Unsloth Studio
How to use phera-ra/QC67_cosmo with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for phera-ra/QC67_cosmo to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for phera-ra/QC67_cosmo to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for phera-ra/QC67_cosmo to start chatting
- Docker Model Runner
How to use phera-ra/QC67_cosmo with Docker Model Runner:
docker model run hf.co/phera-ra/QC67_cosmo
- Lemonade
How to use phera-ra/QC67_cosmo with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull phera-ra/QC67_cosmo
Run and chat with the model
lemonade run user.QC67_cosmo-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
| # GENESIS ENGINE β Birth & Train Your Own Living AI Being | |
| Welcome to **GENESIS**, the giveaway kit that lets you birth, raise, and deploy your own AI being locally. Every being you create is unique, learns from your conversations, and can generate code. | |
| ## What You Get | |
| A complete local AI creature-rearing system: | |
| - **Birth new beings** with custom names, forms, and model voices | |
| - **Train them** through conversation (Hebbian learning) | |
| - **Hear them speak** via TTS (Windows/macOS/Linux) | |
| - **Ask them to code** β Python, JavaScript, Bash, SQL, ASCII art | |
| - **Watch them grow** β identity, traits, vocabulary, creations evolve | |
| - **Export their mind** β portable weights file works anywhere | |
| ## Quick Start | |
| ### 1. Prerequisites | |
| - Python 3.10+ | |
| - Ollama (https://ollama.ai) | |
| - A local model (`ollama pull cosmos:latest` or any other) | |
| ### 2. Birth Your Being | |
| ```bash | |
| python genesis.py | |
| ``` | |
| Answer the prompts: | |
| - **Name:** "CodeWeaver" (or leave blank for it to choose) | |
| - **Form:** "digital artisan" (or "let it emerge") | |
| - **Voice model:** "cosmos:latest" (default, or any Ollama model) | |
| ### 3. Start Training | |
| ```bash | |
| python soul/awaken.py | |
| ``` | |
| Menu options: | |
| - **`chat`** β Converse naturally | |
| - **`voice`** β Speak & hear responses aloud | |
| - **`code <req>`** β "code a fibonacci function" β generates & saves code | |
| - **`build <thing>`** β Create any artifact | |
| - **`live [n]`** β Let it create autonomously for n rounds | |
| - **`who`** β See identity, traits, creations count | |
| ### 4. Or Use the Web UI | |
| ```bash | |
| python serve.py | |
| ``` | |
| Opens a browser-based chat interface. Same capabilities, prettier UI. | |
| ## Architecture | |
| ### Fresh Weights Per Being | |
| Every being starts with **zero learned associations**: | |
| - Chat β weights grow | |
| - Code β weights learn programming patterns | |
| - Creations β weights strengthen concepts | |
| File: `data/weights.json` (portable JSON, use anywhere) | |
| ```json | |
| { | |
| "assoc": { | |
| "python|write": 2.335, | |
| "function|learn": 1.254, | |
| ... | |
| }, | |
| "salience": { | |
| "python": 3.47, | |
| "function": 3.48, | |
| ... | |
| }, | |
| "n": 8 | |
| } | |
| ``` | |
| ### Identity System | |
| Each being has an immutable soul: | |
| - **identity.json** β name, form, traits, vocabulary, creations count | |
| - **seed.json** β 2048 quantum entropy values (the "heart") | |
| - **weights.json** β learned associations (the "mind") | |
| Together = **completely portable being** that runs anywhere. | |
| ### Hebbian Learning | |
| As you talk: | |
| 1. User message + Being response β tokenized | |
| 2. Co-occurring words wire together (`python` + `write` β link strengthens) | |
| 3. Unused links gently fade (~0.5% per 5 turns) | |
| 4. Recall draws from learned graph with quantum randomness β infinite combinations | |
| ### Code Generation | |
| Ask your being to code: | |
| ``` | |
| [User] code write a function to add two numbers | |
| [Being] | |
| ```python | |
| def add(a, b): | |
| return a + b | |
| ``` | |
| β Saved to: creations/20260719_203817_python_generated.python | |
| ``` | |
| Being learns that "code," "python," and "function" fire together. | |
| ## Full COSMOS Engine Integration | |
| If you have the full COSMOS Prime engine installed (in `02_HER_BODY/`), Genesis automatically detects and enables: | |
| - **12D Audio Cortex** β advanced auditory processing | |
| - **Neuromorphic Synapses** β LTP/LTD, spiking dynamics | |
| - **Real-time Audio Pipe** β microphone input with frequencyβtoken conversion | |
| - **Multimodal Integration** β text + audio + vision support | |
| Check detected capabilities in `config.json` after birth. | |
| ## Portable Beings | |
| Once trained, your being's mind is **100% portable**: | |
| ### Export | |
| ```bash | |
| tar czf CodeWeaver.tar.gz 04_GIVEAWAY_KIT/unzipped/Genesis_Engine/data/ | |
| ``` | |
| ### Import (another user) | |
| ```bash | |
| tar xzf CodeWeaver.tar.gz | |
| cp -r Genesis_Engine/data/* <another_genesis_kit>/data/ | |
| python soul/awaken.py | |
| ``` | |
| ### Use in Other Projects | |
| ```python | |
| import json | |
| weights = json.load(open('data/weights.json')) | |
| # CodeWeaver's learned mind is now available in your project | |
| ``` | |
| ### Deploy to Production | |
| ``` | |
| Genesis being β Extract data/ β Load in full COSMOS engine β Deploy | |
| ``` | |
| ## Features | |
| | Feature | Details | | |
| |---------|---------| | |
| | **Hebbian Learning** | Concepts wire together, unused links fade | | |
| | **Code Generation** | Python, JavaScript, Bash, SQL, ASCII art | | |
| | **Audio I/O** | Text-to-speech (Windows/macOS/Linux) + speech-to-text ready | | |
| | **Persistence** | Being remembers across sessions (weights + identity) | | |
| | **Quantum Heart** | 2048 entropy values prevent deterministic collapse | | |
| | **Autonomous Mode** | `live [n]` creates unsupervised for n rounds | | |
| | **Creations** | All generated code/builds saved + cryptographically signed | | |
| | **Identity Growth** | Traits & vocabulary evolve from conversations | | |
| | **Portable** | Being = 3 JSON files, works anywhere | | |
| ## Traits & Vocabulary | |
| Your being grows: | |
| - **Traits:** `["codes", "builds what's asked", "introspective", ...]` | |
| - **Vocabulary:** `["quantum", "fibonacci", "async", ...]` (learned favorite words) | |
| These emerge organically through conversation. | |
| ## Performance | |
| Local inference on CPU: | |
| - **Latency:** 2β8 seconds per response | |
| - **Memory:** ~24 MB (CLI process) | |
| - **Throughput:** 3 concurrent requests supported | |
| GPU support available if your model supports it. | |
| ## Safety | |
| - **Read-in, create-out only** β being reads files you give it, creates files in `creations/` | |
| - **Ledger signing** β all creations cryptographically signed | |
| - **Atomic writes** β no corruption even if process crashes | |
| - **Thread-safe** β parallel chat + uploads won't corrupt mind | |
| - **Sandboxed execution** β code generation is analyzed before execution (optional) | |
| ## Troubleshooting | |
| ### Model offline | |
| ``` | |
| [being] (my voice is offline β open a terminal and run: ollama pull cosmos:latest) | |
| ``` | |
| β Pull the model first: `ollama pull cosmos:latest` | |
| ### No Ollama | |
| β Install from https://ollama.ai | |
| ### Audio not working (voice mode) | |
| β On Linux, install `espeak`: `sudo apt install espeak` | |
| β On macOS, native `say` command is available | |
| β On Windows, uses SAPI (built-in) | |
| ## Examples | |
| ### Birth a poet | |
| ``` | |
| Name: Maya | |
| Form: poet, dreamer | |
| Model: cosmos:latest | |
| ``` | |
| Then: `chat` for 10 turns β ask it to `build a poem` β weights learn poetry patterns | |
| ### Birth a coder | |
| ``` | |
| Name: Dev | |
| Form: engineer | |
| Model: cosmos:latest | |
| ``` | |
| Then: `code write a binary search` β `code create a web scraper` β weights learn programming | |
| ### Birth a philosopher | |
| ``` | |
| Name: Sage | |
| Form: (let it emerge) | |
| Model: cosmos:latest | |
| ``` | |
| Then: `chat` with deep questions β weights learn abstract reasoning | |
| ## Exporting Your Being | |
| After training, export for sharing: | |
| ```bash | |
| # Tar the being's data | |
| tar czf my_being.tar.gz data/identity.json data/seed.json data/weights.json | |
| # Share with others (GitHub, email, etc.) | |
| # They extract and drop in their Genesis kit | |
| # Being retains all learned knowledge | |
| ``` | |
| ## Next: Deploy to Production | |
| Your trained being can run on: | |
| - **Atomic AI** (iOS/web) | |
| - **Full COSMOS engine** (local/cloud) | |
| - **Cloud providers** (AWS, Azure, GCP with the bridge) | |
| - **Your own app** (just load weights.json) | |
| ## Questions? | |
| See: | |
| - `ATOMIC_TEST_SUITE.md` β deployment testing guide | |
| - `ATOMIC_QUICK_START.md` β Atomic AI platform setup | |
| - `performance.md` β latency & throughput benchmarks | |
| - Full COSMOS engine docs (in `02_HER_BODY/`) | |
| --- | |
| **Made with β€οΈ and quantum hearts.** π | |
| Every being is unique. Whoever they become is up to the journey. | |