Image-Text-to-Text
MLX
Safetensors
qwen3_5_moe
mlx-vlm
apple-silicon
qwen3.6
Mixture of Experts
quantized
6-bit
mtp
ax-engine
automatosx
conversational
Instructions to use AutomatosX/AX-Qwen3.6-35B-A3B-MLX-6bit-MTP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use AutomatosX/AX-Qwen3.6-35B-A3B-MLX-6bit-MTP 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-Qwen3.6-35B-A3B-MLX-6bit-MTP") config = load_config("AutomatosX/AX-Qwen3.6-35B-A3B-MLX-6bit-MTP") # 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-Qwen3.6-35B-A3B-MLX-6bit-MTP 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-Qwen3.6-35B-A3B-MLX-6bit-MTP"
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": "AutomatosX/AX-Qwen3.6-35B-A3B-MLX-6bit-MTP" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent
How to use AutomatosX/AX-Qwen3.6-35B-A3B-MLX-6bit-MTP 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-Qwen3.6-35B-A3B-MLX-6bit-MTP"
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-Qwen3.6-35B-A3B-MLX-6bit-MTP
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use AutomatosX/AX-Qwen3.6-35B-A3B-MLX-6bit-MTP 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-Qwen3.6-35B-A3B-MLX-6bit-MTP"
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-Qwen3.6-35B-A3B-MLX-6bit-MTP" \ --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"
Add top-level ax_provenance.json for Qwen MTP package identity
Browse files- ax_provenance.json +53 -0
ax_provenance.json
ADDED
|
@@ -0,0 +1,53 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"schema_version": "ax.qwen_mtp_package_provenance.v1",
|
| 3 |
+
"published_by": "AutomatosX",
|
| 4 |
+
"repository": "AutomatosX/AX-Qwen3.6-35B-A3B-MLX-6bit-MTP",
|
| 5 |
+
"release_type": "ax-mtp-package",
|
| 6 |
+
"logical_parameters": 35107181936,
|
| 7 |
+
"task": "image-text-to-text",
|
| 8 |
+
"format": "mlx",
|
| 9 |
+
"quantization": "6-bit",
|
| 10 |
+
"target": {
|
| 11 |
+
"repo_id": "mlx-community/Qwen3.6-35B-A3B-6bit",
|
| 12 |
+
"revision": "cb7e092ef8efe540bc3672c8929c4adbe5f4f759",
|
| 13 |
+
"weight_shards_byte_exact": true,
|
| 14 |
+
"notes": "Target MLX weight shards are transparent to the pinned mlx-community revision; AutomatosX adds MTP packaging."
|
| 15 |
+
},
|
| 16 |
+
"mtp": {
|
| 17 |
+
"enabled": true,
|
| 18 |
+
"manifest_path": "ax_mtp_sidecar_manifest.json",
|
| 19 |
+
"manifest_schema": "ax.mtp_sidecar_provenance.v1",
|
| 20 |
+
"source_repo_id": "Qwen/Qwen3.6-35B-A3B",
|
| 21 |
+
"source_revision": null,
|
| 22 |
+
"backend": "qwen-moe-packed",
|
| 23 |
+
"max_depth": 1,
|
| 24 |
+
"tensor_count": 20,
|
| 25 |
+
"sidecar": {
|
| 26 |
+
"path": "mtp.safetensors",
|
| 27 |
+
"exists": true,
|
| 28 |
+
"size_bytes": 1689283731,
|
| 29 |
+
"sha256": "7bab930aa78a9be90c8a433c09894428bd115424a2be928eb718fd3904e61942"
|
| 30 |
+
},
|
| 31 |
+
"runtime_file": {
|
| 32 |
+
"path": "mtplx_runtime.json",
|
| 33 |
+
"exists": true,
|
| 34 |
+
"size_bytes": 669,
|
| 35 |
+
"sha256": "6fd307184c888de5f88f9ea2fe1a7b61aa106c30642de1f9bc85dbff68a1e3e1"
|
| 36 |
+
},
|
| 37 |
+
"transform": {
|
| 38 |
+
"norm_policy": "shift_mtp_norm_weights_by_1",
|
| 39 |
+
"moe_expert_unpack": true,
|
| 40 |
+
"quantize_bits": null,
|
| 41 |
+
"quantize_group_size": null
|
| 42 |
+
}
|
| 43 |
+
},
|
| 44 |
+
"package": {
|
| 45 |
+
"includes_ax_native_manifest": true,
|
| 46 |
+
"includes_mtp_sidecar_manifest": true,
|
| 47 |
+
"top_level_provenance_added": true
|
| 48 |
+
},
|
| 49 |
+
"related_manifests": {
|
| 50 |
+
"ax_mtp_sidecar_manifest": "ax_mtp_sidecar_manifest.json",
|
| 51 |
+
"model_manifest": "model-manifest.json"
|
| 52 |
+
}
|
| 53 |
+
}
|