Instructions to use EigenLabs/Qwen3.8-27B-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use EigenLabs/Qwen3.8-27B-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("EigenLabs/Qwen3.8-27B-4bit") config = load_config("EigenLabs/Qwen3.8-27B-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 EigenLabs/Qwen3.8-27B-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 "EigenLabs/Qwen3.8-27B-4bit"
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": "EigenLabs/Qwen3.8-27B-4bit" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent
How to use EigenLabs/Qwen3.8-27B-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 "EigenLabs/Qwen3.8-27B-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 EigenLabs/Qwen3.8-27B-4bit
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use EigenLabs/Qwen3.8-27B-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 "EigenLabs/Qwen3.8-27B-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 "EigenLabs/Qwen3.8-27B-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"
File size: 2,422 Bytes
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library_name: mlx
license: apache-2.0
pipeline_tag: image-text-to-text
base_model:
- Qwen/Qwen3.8-27B
tags:
- mlx
- mlx-vlm
- vision
---
# EigenLabs/Qwen3.8-27B-4bit
This revision is a complete MLX 4-bit Qwen3.8 vision-language model that accepts image, video, and text inputs and generates text.
The **1,847 `language_model.*` tensors are bit-for-bit identical** to [`EigenLabs/Qwen3.8-27B-4bit@eda45ab47f465d08d6558f0353a2346e2eb9d5b3`](https://huggingface.co/EigenLabs/Qwen3.8-27B-4bit/tree/eda45ab47f465d08d6558f0353a2346e2eb9d5b3). The 333 `vision_tower.*` tensors and multimodal processor assets come from [`mlx-community/Qwen3.8-27B-4bit@3e6447f082e89cc7f0bc6e5441afd38dfce760ff`](https://huggingface.co/mlx-community/Qwen3.8-27B-4bit/tree/3e6447f082e89cc7f0bc6e5441afd38dfce760ff), converted from the official [`Qwen/Qwen3.8-27B@1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0`](https://huggingface.co/Qwen/Qwen3.8-27B/tree/1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0) source. Tensor dtype, shape, and raw bytes were checked before publication.
The immutable challenge revision [`eda45ab47f465d08d6558f0353a2346e2eb9d5b3`](https://huggingface.co/EigenLabs/Qwen3.8-27B-4bit/tree/eda45ab47f465d08d6558f0353a2346e2eb9d5b3) remains available and is text-only because it has no vision tower or processor assets. Multi-token prediction (MTP) is intentionally **not embedded** in this repository; the MTP artifact remains separate.
## mlx-vlm
```bash
pip install -U mlx-vlm
mlx_vlm.generate \
--model EigenLabs/Qwen3.8-27B-4bit \
--image /path/to/image.jpg \
--prompt "Describe this image." \
--max-tokens 256
```
Pin the immutable Hub commit shown in this model's history for reproducible deployment.
## Darkbloom
This is the Hugging Face source artifact consumed by Darkbloom's in-process MLX VLM runtime. Darkbloom providers deploy only catalog-approved, immutable model revisions and verify their manifests before loading. Updating this repository alone does not register the model in the Darkbloom catalog or activate provider traffic.
After a Darkbloom catalog release pins the immutable Hub commit and publishes its verified manifest, a provider can discover and download that release:
```bash
darkbloom models catalog
darkbloom models download <catalog-model-id>
darkbloom start --foreground
```
`<catalog-model-id>` is assigned by the Darkbloom catalog; it is not the Hugging Face repository name.
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