Instructions to use ilyakam/Geer-Ornith-1.0-35B-A3B-4-8bit-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ilyakam/Geer-Ornith-1.0-35B-A3B-4-8bit-MLX with MLX:

# Make sure mlx-vlm is installed
# pip install --upgrade mlx-vlm

from mlx_vlm import load, generate
from mlx_vlm.prompt_utils import apply_chat_template
from mlx_vlm.utils import load_config

# Load the model
model, processor = load("ilyakam/Geer-Ornith-1.0-35B-A3B-4-8bit-MLX")
config = load_config("ilyakam/Geer-Ornith-1.0-35B-A3B-4-8bit-MLX")

# Prepare input
image = ["http://images.cocodataset.org/val2017/000000039769.jpg"]
prompt = "Describe this image."

# Apply chat template
formatted_prompt = apply_chat_template(
    processor, config, prompt, num_images=1
)

# Generate output
output = generate(model, processor, formatted_prompt, image)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps Settings
LM Studio

How to use ilyakam/Geer-Ornith-1.0-35B-A3B-4-8bit-MLX with Pi:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "ilyakam/Geer-Ornith-1.0-35B-A3B-4-8bit-MLX"

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "mlx-lm": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "ilyakam/Geer-Ornith-1.0-35B-A3B-4-8bit-MLX"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent

How to use ilyakam/Geer-Ornith-1.0-35B-A3B-4-8bit-MLX with Hermes Agent:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "ilyakam/Geer-Ornith-1.0-35B-A3B-4-8bit-MLX"

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 ilyakam/Geer-Ornith-1.0-35B-A3B-4-8bit-MLX

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use ilyakam/Geer-Ornith-1.0-35B-A3B-4-8bit-MLX with OpenClaw:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "ilyakam/Geer-Ornith-1.0-35B-A3B-4-8bit-MLX"

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 "ilyakam/Geer-Ornith-1.0-35B-A3B-4-8bit-MLX" \
  --custom-provider-id mlx-lm \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

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

Geer-Ornith-1.0-35B-A3B-4-8bit-MLX

File size: 798 Bytes

1ed82bf

schema_version = 1
id = "ornith-1.0-35b-4-8bit"
display_name = "Geer Ornith 1.0 35B-A3B (4/8-bit MLX)"

[source]
repo_id = "deepreinforce-ai/Ornith-1.0-35B"
revision = "5df2ed3f675c7beaa490328cc70bb573b65fb660"
expected_bytes = 70250400102
license = "MIT"
license_evidence_url = "https://huggingface.co/deepreinforce-ai/Ornith-1.0-35B/blob/5df2ed3f675c7beaa490328cc70bb573b65fb660/README.md"

[conversion]
transform = "qwen3_5_moe_unfused_experts"
dtype = "bfloat16"
mlx = "0.32.0"
mlx_lm = "0.31.3"
mlx_vlm = "0.6.3"
huggingface_hub = "1.24.0"
hf_xet = "1.5.2"
safetensors = "0.8.0"

[quantization]
enabled = true
strategy = "routed_experts_4bit_protected_text_8bit"
mode = "affine"
bits = 4
high_bits = 8
group_size = 64

[output]
expected_architecture = "qwen3_5_moe"
preserve_multimodal = true