Image-Text-to-Text
MLX
Safetensors
English
qwen2_vl
chat
abliterated
uncensored
conversational
8-bit precision
Instructions to use EZCon/Qwen2-VL-2B-Instruct-abliterated-8bit-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use EZCon/Qwen2-VL-2B-Instruct-abliterated-8bit-mlx 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("EZCon/Qwen2-VL-2B-Instruct-abliterated-8bit-mlx") config = load_config("EZCon/Qwen2-VL-2B-Instruct-abliterated-8bit-mlx") # 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
| { | |
| "bos_token_id": 151643, | |
| "pad_token_id": 151643, | |
| "do_sample": true, | |
| "eos_token_id": [ | |
| 151645, | |
| 151643 | |
| ], | |
| "repetition_penalty": 1.0, | |
| "temperature": 0.01, | |
| "top_p": 0.001, | |
| "top_k": 1, | |
| "transformers_version": "4.37.0" | |
| } | |