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

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

QC67_cosmo

File size: 3,363 Bytes

20edc0f

{
    "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":  [
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                      "role":  "primary"
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                  {
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                  {
                      "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",
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              ],
    "notes":  "Manifest generated by Copilot CLI. This file describes the checkpoint artifacts, their sizes and SHA256 sums where available. No weights were modified."
}