Image-Text-to-Text
MLX
Safetensors
English
idefics3
text-generation
screen-parsing
ui-understanding
object-detection
grounding
web
screentag
docling
granite
quantized
apple-silicon
conversational
4-bit precision
Instructions to use olragon/ScreenVLM-MLX-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use olragon/ScreenVLM-MLX-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("olragon/ScreenVLM-MLX-4bit") config = load_config("olragon/ScreenVLM-MLX-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
| { | |
| "add_prefix_space": false, | |
| "backend": "tokenizers", | |
| "bos_token": "<|start_of_role|>", | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|end_of_text|>", | |
| "errors": "replace", | |
| "extra_special_tokens": [ | |
| "<fake_token_around_image>", | |
| "<image>", | |
| "<end_of_utterance>" | |
| ], | |
| "is_local": true, | |
| "local_files_only": false, | |
| "model_max_length": 8192, | |
| "pad_token": "<|end_of_text|>", | |
| "padding_side": "left", | |
| "processor_class": "Idefics3Processor", | |
| "tokenizer_class": "GPT2Tokenizer", | |
| "unk_token": "<|unk|>" | |
| } | |