I would like to fine tune a model on my own data. However the model is distributed by tflite format. Is there anyway to extract the model architecture and parameters out of the tflite file?
How to do fine tuning on TFlite model
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I'm not sure to understand what you need. But if you want to know the exact architecture of your model you can use neutron to find out.
You will get something like the this : 
And for your information TensorFlow Lite is not meant to be finetuned. You need to finetune a classic TensorFlow model and then convert it to TensorFlow Lite.
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One approach could be to convert the TFLite file to another format, and import into a deep learning framework that supports training.
Something like ONNX, using tflite2onnx, and then import into a framework of your choice. Not all frameworks can import from ONNX (e.g. PyTorch). I believe you can train with ONNXRuntime, and MXNet. Unsure if you can train using TensorFlow.