Image-Text-to-Text
MLX
Safetensors
English
Chinese
qwen3_5
qwen3.8
quantized
vision-language
mtp
f16-source
conversational
8-bit precision
Instructions to use npario/Qwen3.8-27B-Uncensored-OrcaRouter-MLX-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use npario/Qwen3.8-27B-Uncensored-OrcaRouter-MLX-8bit 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("npario/Qwen3.8-27B-Uncensored-OrcaRouter-MLX-8bit") config = load_config("npario/Qwen3.8-27B-Uncensored-OrcaRouter-MLX-8bit") # 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 npario/Qwen3.8-27B-Uncensored-OrcaRouter-MLX-8bit with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "npario/Qwen3.8-27B-Uncensored-OrcaRouter-MLX-8bit"
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": "npario/Qwen3.8-27B-Uncensored-OrcaRouter-MLX-8bit" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent
How to use npario/Qwen3.8-27B-Uncensored-OrcaRouter-MLX-8bit 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 "npario/Qwen3.8-27B-Uncensored-OrcaRouter-MLX-8bit"
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 npario/Qwen3.8-27B-Uncensored-OrcaRouter-MLX-8bit
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use npario/Qwen3.8-27B-Uncensored-OrcaRouter-MLX-8bit with OpenClaw:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "npario/Qwen3.8-27B-Uncensored-OrcaRouter-MLX-8bit"
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 "npario/Qwen3.8-27B-Uncensored-OrcaRouter-MLX-8bit" \ --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"
Download LINEAGE.json from npario/Qwen3.8-27B-Uncensored-OrcaRouter-MLX-8bit: direct link, hf CLI and curl.
- Browser
- Download file 1.14 kB
-
https://huggingface.co/npario/Qwen3.8-27B-Uncensored-OrcaRouter-MLX-8bit/resolve/main/LINEAGE.json
- Command line
-
hf download hf://npario/Qwen3.8-27B-Uncensored-OrcaRouter-MLX-8bit/LINEAGE.json
-
curl -L -o LINEAGE.json https://huggingface.co/npario/Qwen3.8-27B-Uncensored-OrcaRouter-MLX-8bit/resolve/main/LINEAGE.json
1.14 kB
| { | |
| "base_model": "Qwen/Qwen3.8-27B", | |
| "baseline_revision": "13137955862a8aa7de46aaa87dbc3603f6520931", | |
| "bits": 8, | |
| "destination_repo": "chimingw/Qwen3.8-27B-Uncensored-OrcaRouter-MLX-8bit", | |
| "group_size": 64, | |
| "independent_from_floating_parent": true, | |
| "mode": "affine", | |
| "precision_parent": "direct floating F16 GGUF plus source-matched floating mmproj; no FP8 intermediate", | |
| "public_deletions_authorized": false, | |
| "schema": 2, | |
| "source_files": [ | |
| { | |
| "path": "Qwen3.8-27B-Uncensored-F16-00001-of-00002.gguf", | |
| "sha256": "578926d4e6d94281e95a48d8e154c4667061a669e9016f2aa2b15101ab4363dc", | |
| "size": 27908108288 | |
| }, | |
| { | |
| "path": "Qwen3.8-27B-Uncensored-F16-00002-of-00002.gguf", | |
| "sha256": "c15e78454caec46b19dae22fa6915a9e77b917e7cceffdc64c265801f4eaa1f1", | |
| "size": 26749625920 | |
| }, | |
| { | |
| "path": "mmproj-Qwen3.8-27B-Uncensored-f16.gguf", | |
| "sha256": "add205b7bfdb3f71f6da36b0a82aa20928dd829a920878c602628cdfbebc5288", | |
| "size": 931145984 | |
| } | |
| ], | |
| "source_repo": "orcarouter/Qwen3.8-27B-Uncensored-GGUF", | |
| "source_revision": "402c3e0a64d77880f55ab096c5b7597ef85162ab" | |
| } | |