Instructions to use prithivMLmods/Zenith-9B-CodeCore-Merge-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use prithivMLmods/Zenith-9B-CodeCore-Merge-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("prithivMLmods/Zenith-9B-CodeCore-Merge-MLX")
config = load_config("prithivMLmods/Zenith-9B-CodeCore-Merge-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 prithivMLmods/Zenith-9B-CodeCore-Merge-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 "prithivMLmods/Zenith-9B-CodeCore-Merge-MLX"

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "mlx-lm": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "prithivMLmods/Zenith-9B-CodeCore-Merge-MLX"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent

How to use prithivMLmods/Zenith-9B-CodeCore-Merge-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 "prithivMLmods/Zenith-9B-CodeCore-Merge-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 prithivMLmods/Zenith-9B-CodeCore-Merge-MLX

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use prithivMLmods/Zenith-9B-CodeCore-Merge-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 "prithivMLmods/Zenith-9B-CodeCore-Merge-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 "prithivMLmods/Zenith-9B-CodeCore-Merge-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"

prithivMLmods commited on 13 days ago

Commit

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@@ -16,6 +16,12 @@ base_model:
 license: apache-2.0
 ---
 ## Repository layout
 ```plaintext
@@ -157,4 +163,15 @@ output = generate(
     temperature=0.0
 )
 print(output.text)
-```

 license: apache-2.0
 ---
+# **Zenith-9B-CodeCore-Merge-MLX**
+> Zenith-9B-CodeCore-Merge is a merged 9B-parameter coding and reasoning model designed for long-horizon coding tasks, agentic coding, and agentic reasoning. It is built by merging [Qwen3.5-9B](https://huggingface.co/Qwen/Qwen3.5-9B) as the base model with [OxCoder-9B](https://huggingface.co/OrionLLM/OxCoder-9B), [Qwopus3.5-9B-Coder](https://huggingface.co/Jackrong/Qwopus3.5-9B-Coder), and [Ornith-1.5-9B](https://huggingface.co/ornith-ai/Ornith-1.5-9B), combining their capabilities for code generation, multi-step problem solving, instruction following, and autonomous coding workflows. The model is intended for complex software-engineering tasks that require sustained reasoning across multiple steps, code understanding, modification, debugging, and tool-oriented agentic workflows. This model is experimental and may generate artifacts.
+- *GGUF: [Zenith-9B-CodeCore-Merge-GGUF](https://huggingface.co/prithivMLmods/Zenith-9B-CodeCore-Merge-GGUF). Note: The Multi-Token Prediction (MTP) heads are not preserved in this format. The model runs as a standard single-token-per-step autoregressive decoder.*
 ## Repository layout
 ```plaintext
     temperature=0.0
 )
 print(output.text)
+```
+## License and Attribution
+This model is based on and/or incorporates the following open-source projects and models:
+* **Qwen3.5-9B (Base):** [https://huggingface.co/Qwen/Qwen3.5-9B](https://huggingface.co/Qwen/Qwen3.5-9B)
+* **Zenith-9B-CodeCore-Merge:** [https://huggingface.co/prithivMLmods/Zenith-9B-CodeCore-Merge](https://huggingface.co/prithivMLmods/Zenith-9B-CodeCore-Merge)
+* **mlx-vlm:** [https://github.com/Blaizzy/mlx-vlm](https://github.com/Blaizzy/mlx-vlm)
+* **MLX:** [https://github.com/ml-explore/mlx](https://github.com/ml-explore/mlx)
+This model is released under the [Apache License 2.0](https://huggingface.co/datasets/choosealicense/licenses/blob/main/markdown/apache-2.0.md).