Image-Text-to-Text
MLX
Safetensors
diffusion_gemma
apple-silicon
diffusion-gemma
mixture-of-experts
quantized
4-bit precision
mirror
automatosx
ax-engine
conversational
Instructions to use AutomatosX/AX-DiffusionGemma-26B-A4B-IT-MLX-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use AutomatosX/AX-DiffusionGemma-26B-A4B-IT-MLX-4bit 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("AutomatosX/AX-DiffusionGemma-26B-A4B-IT-MLX-4bit") config = load_config("AutomatosX/AX-DiffusionGemma-26B-A4B-IT-MLX-4bit") # 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
- Pi
How to use AutomatosX/AX-DiffusionGemma-26B-A4B-IT-MLX-4bit with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "AutomatosX/AX-DiffusionGemma-26B-A4B-IT-MLX-4bit"
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": "AutomatosX/AX-DiffusionGemma-26B-A4B-IT-MLX-4bit" } ] } } }Run Pi
# Start Pi in your project directory: pi
- OpenClaw new
How to use AutomatosX/AX-DiffusionGemma-26B-A4B-IT-MLX-4bit with OpenClaw:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "AutomatosX/AX-DiffusionGemma-26B-A4B-IT-MLX-4bit"
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 "AutomatosX/AX-DiffusionGemma-26B-A4B-IT-MLX-4bit" \ --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"
- Hermes Agent
How to use AutomatosX/AX-DiffusionGemma-26B-A4B-IT-MLX-4bit 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 "AutomatosX/AX-DiffusionGemma-26B-A4B-IT-MLX-4bit"
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 AutomatosX/AX-DiffusionGemma-26B-A4B-IT-MLX-4bit
Run Hermes
hermes
- Atomic Chat
Correct logical model size information
Browse filesDocument the logical target parameter count and, where needed, correct the Safetensors index metadata so packed quantized storage is not mistaken for model size. Weight files and shard weight maps are unchanged.
- README.md +12 -4
- ax_provenance.json +15 -3
- model.safetensors.index.json +3 -2
README.md
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# AX DiffusionGemma 26B-A4B IT MLX 4-bit
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> **Transparent upstream mirror — AutomatosX made no model changes.**
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This is a revision-pinned,
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[mlx-community/diffusiongemma-26B-A4B-it-4bit](https://huggingface.co/mlx-community/diffusiongemma-26B-A4B-it-4bit)
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at commit `a7a81407613811e8ba63af92ac0d852b809e191f`.
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template, or generation settings. The MLX conversion and quantization were
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performed upstream by MLX Community with `mlx-vlm` 0.6.3. AutomatosX adds only
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this mirror documentation, the preserved upstream model card, a copy of the
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declared license,
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## Model details
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`UPSTREAM_README.md` preserves the original MLX Community model card.
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`ax_provenance.json` pins the source commit and records SHA-256 values and sizes
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for every mirrored artifact. All
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card are byte-identical to the pinned
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This repository exists for revision-pinned cataloging and convenient discovery;
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it does not represent a new model, conversion, quantization, or benchmark claim
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# AX DiffusionGemma 26B-A4B IT MLX 4-bit
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> **Parameter count:** approximately 25.82B logical parameters (26B total,
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> approximately 4B active per token). `4-bit` is the quantization precision,
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> not a 4B model-size claim.
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> **Transparent upstream mirror — AutomatosX made no model changes.**
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This is a revision-pinned, transparent mirror of
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[mlx-community/diffusiongemma-26B-A4B-it-4bit](https://huggingface.co/mlx-community/diffusiongemma-26B-A4B-it-4bit)
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at commit `a7a81407613811e8ba63af92ac0d852b809e191f`.
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template, or generation settings. The MLX conversion and quantization were
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performed upstream by MLX Community with `mlx-vlm` 0.6.3. AutomatosX adds only
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this mirror documentation, the preserved upstream model card, a copy of the
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declared license, machine-readable provenance, and a `total_parameters` field
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in the shard index so the Hub does not mistake packed 4-bit storage for the
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logical model size.
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## Model details
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`UPSTREAM_README.md` preserves the original MLX Community model card.
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`ax_provenance.json` pins the source commit and records SHA-256 values and sizes
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for every mirrored artifact. All weight shards and all source artifacts other
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than the replaced model card and shard index are byte-identical to the pinned
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upstream revision. In the index, `weight_map` and `total_size` remain unchanged;
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only the logical `total_parameters` metadata field was added.
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This repository exists for revision-pinned cataloging and convenient discovery;
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it does not represent a new model, conversion, quantization, or benchmark claim
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ax_provenance.json
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"source": {
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"repo_id": "mlx-community/diffusiongemma-26B-A4B-it-4bit",
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"revision": "a7a81407613811e8ba63af92ac0d852b809e191f",
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"model_artifacts_byte_exact":
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"upstream_readme_preserved_as": "UPSTREAM_README.md",
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"upstream_readme_sha256": "ad3262ee1b00cc856307a469e710991295712fee20480789aa522152785866c8"
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},
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"merged": false,
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"converted": false,
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"requantized": false,
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"mtp_added": false
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},
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"quantization": {
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"format": "mlx",
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"README.md",
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"UPSTREAM_README.md",
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"LICENSE",
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"ax_provenance.json"
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"excluded_local_only_files": [],
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"mtp": false
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}
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"source": {
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"repo_id": "mlx-community/diffusiongemma-26B-A4B-it-4bit",
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"revision": "a7a81407613811e8ba63af92ac0d852b809e191f",
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"model_artifacts_byte_exact": false,
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"weight_shards_byte_exact": true,
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"index_weight_map_byte_exact": true,
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"upstream_readme_preserved_as": "UPSTREAM_README.md",
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"upstream_readme_sha256": "ad3262ee1b00cc856307a469e710991295712fee20480789aa522152785866c8"
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},
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"merged": false,
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"converted": false,
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"requantized": false,
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"mtp_added": false,
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"index_metadata_modified": true
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},
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"quantization": {
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"format": "mlx",
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"README.md",
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"UPSTREAM_README.md",
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"LICENSE",
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"ax_provenance.json",
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"model.safetensors.index.json:metadata.total_parameters"
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],
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"destination_index": {
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"path": "model.safetensors.index.json",
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"size_bytes": 165404,
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"sha256": "2b9d39e640173a25acd648ef4d0e98ae4cd06e90b6d6e0b4c0f22111491835d3",
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"total_parameters": 25823778864,
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"source_weight_map_unchanged": true,
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"source_total_size_unchanged": true
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},
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"excluded_local_only_files": [],
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"mtp": false
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}
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model.safetensors.index.json
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{
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"metadata": {
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"total_size": 16542844632
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"weight_map": {
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"model.decoder.embed_tokens.biases": "model-00001-of-00004.safetensors",
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"model.encoder.vision_tower.std_bias": "model-00004-of-00004.safetensors",
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"model.encoder.vision_tower.std_scale": "model-00004-of-00004.safetensors"
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}
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{
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"metadata": {
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"total_size": 16542844632,
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"total_parameters": 25823778864
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},
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"weight_map": {
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"model.decoder.embed_tokens.biases": "model-00001-of-00004.safetensors",
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"model.encoder.vision_tower.std_bias": "model-00004-of-00004.safetensors",
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"model.encoder.vision_tower.std_scale": "model-00004-of-00004.safetensors"
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}
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}
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