#cplusplus#arm#baidu#deep_learning#embedded#fpga#mali#mdl#mobile#mobile_deep_learning#neural_network
Paddle Lite is a lightweight, high-performance deep learning inference framework designed to run AI models efficiently on mobile, embedded, and edge devices. It supports multiple platforms like Android, iOS, Linux, Windows, and macOS, and languages including C++, Java, and Python. You can easily convert models from other frameworks to PaddlePaddle format, optimize them for faster and smaller deployment, and run them with ready-made examples. This helps you deploy AI applications quickly on various devices with low memory use and fast speed, making it ideal for real-time, resource-limited environments. It also supports many hardware accelerators for better performance.
https://github.com/PaddlePaddle/Paddle-Lite
Choc Chip Banana Bread ✨🍌🤎
Ingredients:
* 3 large ripe bananas (360–380 g)
* 130 g unsalted butter (will reduce to \~115 g once browned)
* 180 g dark brown sugar (+ 1–2 tbsp for topping)
* 2 large eggs
* 250 g plain flour
* 1 tsp baking soda
* ½ tsp salt
* ½ tsp cinnamon
* 70–100 g dark chocolate, chopped
* Optional: chopped nuts
#dinner
@dishes
My Kind of Girl Dinner 😮💨🍚🥒
Ingredients:
For the salmon:
* 2 salmon fillets (skin removed, cut into cubes)
* 2 tbsp soy sauce
* 1 tbsp oyster sauce
* 1 tsp brown sugar
* 2 tsp minced garlic
* 1 tbsp sriracha
* ¼ tsp chili flakes
For the rice & toppings:
* 100 g sushi rice (cooked)
* 1 tsp apple cider vinegar
* ½ tsp salt
* ½ tsp sugar
* Pinch of chili flakes
* ¼ cucumber, thinly sliced
* ¼ small onion, thinly sliced
* Handful of edamame (cooked)
* Black & white sesame seeds, for topping
#dinner
@dishes