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  This model provides [HuggingFaceTB/SmolVLM-256M-Instruct](https://huggingface.co/HuggingFaceTB/SmolVLM-256M-Instruct) model in TFLite format.
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- You can use this model with [AI Edge Cpp Example](https://github.com/google-ai-edge/ai-edge-torch/tree/main/ai_edge_torch/generative/examples/cpp).
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- You need to slightly modify cpp pipeline, just send image tensor as input (see COLAB example below).
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  Please note that, at the moment, [AI Edge Torch](https://github.com/google-ai-edge/ai-edge-torch/tree/main/ai_edge_torch/generative/examples) VLMS not supported
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  on [MediaPipe LLM Inference API](https://ai.google.dev/edge/mediapipe/solutions/genai/llm_inference),
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  for example [qwen_vl model](https://github.com/google-ai-edge/ai-edge-torch/tree/main/ai_edge_torch/generative/examples/qwen_vl),
 
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  This model provides [HuggingFaceTB/SmolVLM-256M-Instruct](https://huggingface.co/HuggingFaceTB/SmolVLM-256M-Instruct) model in TFLite format.
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+ You can use this model with [Custom Cpp Pipiline](https://github.com/dragynir/ai-edge-torch-smalvlm/tree/dev/ai_edge_torch/generative/examples/cpp_image)
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+ or run with python pipeline (see COLAB example below).
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  Please note that, at the moment, [AI Edge Torch](https://github.com/google-ai-edge/ai-edge-torch/tree/main/ai_edge_torch/generative/examples) VLMS not supported
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  on [MediaPipe LLM Inference API](https://ai.google.dev/edge/mediapipe/solutions/genai/llm_inference),
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  for example [qwen_vl model](https://github.com/google-ai-edge/ai-edge-torch/tree/main/ai_edge_torch/generative/examples/qwen_vl),