Instructions to use EigenLabs/Qwen3.8-27B-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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

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"

gajesh commited on 19 days ago

Commit

bbeabc6

verified ·

1 Parent(s): 2f330b9

Finalize complete Qwen3.8 VLM with pinned EigenLabs provenance

Browse files

Complete verified 2,180-tensor VLM snapshot: 1,847 language_model tensors bitwise pinned to EigenLabs/Qwen3.8-27B-4bit@eda45ab47f465d08d6558f0353a2346e2eb9d5b3; 333 vision_tower tensors and processor assets pinned to mlx-community/Qwen3.8-27B-4bit@3e6447f082e89cc7f0bc6e5441afd38dfce760ff from Qwen/Qwen3.8-27B@1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0. MTP remains separate. Uses the canonical mlx_vlm CLI in the model card.

Files changed (1) hide show

README.md +1 -1

README.md CHANGED Viewed

@@ -23,7 +23,7 @@ The immutable challenge revision [`eda45ab47f465d08d6558f0353a2346e2eb9d5b3`](ht
 ```bash
 pip install -U mlx-vlm
-python -m mlx_vlm.generate \
   --model EigenLabs/Qwen3.8-27B-4bit \
   --image /path/to/image.jpg \
   --prompt "Describe this image." \

 ```bash
 pip install -U mlx-vlm
+mlx_vlm generate \
   --model EigenLabs/Qwen3.8-27B-4bit \
   --image /path/to/image.jpg \
   --prompt "Describe this image." \