Model Details
Full Model IDlmstudio-community/Qwen3.8-27B-MLX-4bit
Pipeline / Taskimage-text-to-text
Librarytransformers
Downloads (all-time)3.7M
Likes111
Last Modified8/14/2026
Author / Orglmstudio-community
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("image-text-to-text", model="lmstudio-community/Qwen3.8-27B-MLX-4bit")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerssafetensorsqwen3_5image-text-to-textmlxconversationalbase_model:Qwen/Qwen3.8-27Bbase_model:quantized:Qwen/Qwen3.8-27Blicense:apache-2.0endpoints_compatible4-bitregion:us
More image-text-to-text Models
See all →🚀 Use This Model
Access model files, inference API, and full documentation on Hugging Face.
Open on Hugging Face →Browse Model Files ↗← Browse All Models🤖 Task: image-text-to-text
This model is designed for the image-text-to-text task. Explore more models for this use case.
All image-text-to-text Models →📊 Popularity
⬇ Downloads3.7M
❤️ Community Likes111
🛠️ Requirements
- →Install: pip install transformers
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.