Instructions to use EZCon/SmolVLM2-2.2B-Instruct-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use EZCon/SmolVLM2-2.2B-Instruct-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/SmolVLM2-2.2B-Instruct-mlx") config = load_config("EZCon/SmolVLM2-2.2B-Instruct-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
- Atomic Chat
File size: 848 Bytes
f6cd5ac | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | {
"add_prefix_space": false,
"backend": "tokenizers",
"bos_token": "<|im_start|>",
"clean_up_tokenization_spaces": false,
"end_of_utterance_token": "<end_of_utterance>",
"eos_token": "<end_of_utterance>",
"fake_image_token": "<fake_token_around_image>",
"global_image_token": "<global-img>",
"image_token": "<image>",
"is_local": true,
"legacy": false,
"local_files_only": false,
"model_max_length": 16384,
"model_specific_special_tokens": {
"end_of_utterance_token": "<end_of_utterance>",
"fake_image_token": "<fake_token_around_image>",
"global_image_token": "<global-img>",
"image_token": "<image>"
},
"pad_token": "<|im_end|>",
"processor_class": "SmolVLMProcessor",
"tokenizer_class": "TokenizersBackend",
"truncation_side": "left",
"unk_token": "<|endoftext|>",
"vocab_size": 49152
}
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