Text Generation
PyTorch
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English
quantum
quantum-entropy
from-scratch
char-level
cosmic-synapse-theory
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llama-cpp
continual-learning
reproducible-seed
open-science
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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
Invalid JSON:Unexpected token '', "{
"m"... is not valid JSON
| { | |
| "model_name": "QC67_cosmo", | |
| "architecture": "COSMOS design (custom 54D transformer with CST, Hebbian plasticity, ChaosOscillators, persistent memory)", | |
| "license": "cc-by-4.0", | |
| "repository": "https://huggingface.co/phera-ra/QC67_cosmo", | |
| "commits": { | |
| "readme": "https://huggingface.co/phera-ra/QC67_cosmo/commit/5c5be2b6c5884b3d42310157e0e3ba16d393cac0", | |
| "cosmos_best": "https://huggingface.co/phera-ra/QC67_cosmo/commit/2293c13a12d676a676f504ee77fd1b8d96ce7f06", | |
| "uploaded_gguf": "deleted_or_prior_commit" | |
| }, | |
| "uploaded_at": "2026-07-19T01:36:11-07:00", | |
| "tested": "Local: works with Atomic runtime (user confirmed)", | |
| "files": [ | |
| { | |
| "path": "C:\\Users\\corys\\OneDrive\\Desktop\\COSMOS_MASTER\\02_HER_BODY\\Cosmos_code\\Cosmos\\checkpoints\\cosmos\\cosmos_best.pt", | |
| "filename": "cosmos_best.pt", | |
| "size": 134511228, | |
| "sha256": "850CF3EB140693DF57B7D3EA05EE3D1F74FB248C6DDDB31669CE576246FB64D6", | |
| "format": "pt", | |
| "role": "primary" | |
| }, | |
| { | |
| "path": "C:\\Users\\corys\\OneDrive\\Desktop\\COSMOS_MASTER\\02_HER_BODY\\Cosmos_code\\Cosmos\\checkpoints\\cosmos\\cosmos_play.pt", | |
| "filename": "cosmos_play.pt", | |
| "size": 134511228, | |
| "sha256": "98849BD28352706BF545D94425B0CE111A4D7314D10E9EF9B289115A14BF54B9", | |
| "format": "pt", | |
| "role": "playground" | |
| }, | |
| { | |
| "path": "C:\\Users\\corys\\OneDrive\\Desktop\\COSMOS_MASTER\\02_HER_BODY\\Cosmos_code\\Cosmos\\checkpoints\\cosmos\\cosmos_sandbox.pt", | |
| "filename": "cosmos_sandbox.pt", | |
| "size": 134511030, | |
| "sha256": "34A09078AC7AF8C631F947920657F575FC76C8B7B9C1556F20978402DEE04FC4", | |
| "format": "pt", | |
| "role": "sandbox" | |
| }, | |
| { | |
| "path": "C:\\Users\\corys\\.copilot\\session-state\\198b21fd-8d80-40a5-9716-dbb75e650375\\\\files\\\\README_with_frontmatter.md", | |
| "filename": "README_with_frontmatter.md", | |
| "size": 2423, | |
| "sha256": "D00D56C2AA8391A199278A23C6D82DAF44BC61F161F3BEB1E6CC414967E418FD", | |
| "format": "md", | |
| "role": "readme" | |
| }, | |
| { | |
| "path": "C:\\Users\\corys\\.copilot\\session-state\\198b21fd-8d80-40a5-9716-dbb75e650375\\\\files\\\\LICENSE_CC_BY_4.0.txt", | |
| "filename": "LICENSE_CC_BY_4.0.txt", | |
| "size": 467, | |
| "sha256": "FD0D92F70E5EF1ECE3170B38D1B4E32F6B14D2FA24AB43E06CBD6EED3DA04034", | |
| "format": "txt", | |
| "role": "license" | |
| } | |
| ], | |
| "notes": "Manifest generated by Copilot CLI. This file describes the checkpoint artifacts, their sizes and SHA256 sums where available. No weights were modified." | |
| } | |