Instructions to use open-nhe/Elysium-X-500-FR-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use open-nhe/Elysium-X-500-FR-GGUF 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 open-nhe/Elysium-X-500-FR-GGUF:Q8_0
# Run inference directly in the terminal:
llama cli -hf open-nhe/Elysium-X-500-FR-GGUF:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf open-nhe/Elysium-X-500-FR-GGUF:Q8_0
# Run inference directly in the terminal:
llama cli -hf open-nhe/Elysium-X-500-FR-GGUF:Q8_0

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 open-nhe/Elysium-X-500-FR-GGUF:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf open-nhe/Elysium-X-500-FR-GGUF:Q8_0

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 open-nhe/Elysium-X-500-FR-GGUF:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf open-nhe/Elysium-X-500-FR-GGUF:Q8_0

Use Docker

docker model run hf.co/open-nhe/Elysium-X-500-FR-GGUF:Q8_0

LM Studio
Jan
Ollama
How to use open-nhe/Elysium-X-500-FR-GGUF with Ollama:
```
ollama run hf.co/open-nhe/Elysium-X-500-FR-GGUF:Q8_0
```
Unsloth Desktop

How to use open-nhe/Elysium-X-500-FR-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf open-nhe/Elysium-X-500-FR-GGUF:Q8_0

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "open-nhe/Elysium-X-500-FR-GGUF:Q8_0"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use open-nhe/Elysium-X-500-FR-GGUF with Docker Model Runner:
```
docker model run hf.co/open-nhe/Elysium-X-500-FR-GGUF:Q8_0
```

Lemonade

How to use open-nhe/Elysium-X-500-FR-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull open-nhe/Elysium-X-500-FR-GGUF:Q8_0

Run and chat with the model

lemonade run user.Elysium-X-500-FR-GGUF-Q8_0

List all available models

lemonade list

Hermes Agent

How to use open-nhe/Elysium-X-500-FR-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf open-nhe/Elysium-X-500-FR-GGUF:Q8_0

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default open-nhe/Elysium-X-500-FR-GGUF:Q8_0

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use open-nhe/Elysium-X-500-FR-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf open-nhe/Elysium-X-500-FR-GGUF:Q8_0

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "open-nhe/Elysium-X-500-FR-GGUF:Q8_0" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

🌌 Elysium X 500 FR - GGUF Q8_0

Q8_0 GGUF of the released Elysium X 500 FR: Qwen2.5-1.5B-Instruct with the run-1 LoRA adapter merged in (fp16), converted with llama.cpp. File: Elysium-X-500-FR-Q8_0.gguf, about 1.65 GB. It runs on CPU with llama.cpp.

Not separately evaluated. The numbers on the main card (open-nhe/Elysium-X-500-FR) were measured on the LoRA adapter, not on this file. Quantisation can shift a few answers. We have not scored this GGUF on the test set. An earlier GGUF of the previous checkpoint had its own sample evaluation; that is removed because it described different weights.

The model reads a short conversation and returns JSON naming one or more of 500 emotion coordinates with a strength. Details, honest numbers, sources and licences are on the main card.

Licence: CC BY-NC-SA 4.0, non-commercial. The Qwen2.5 base model is Apache-2.0 and keeps its own licence. See the main card for source-data licences.