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Source channel @githubtrending · Post #14686 · May 8
#python#asr#deeplearning#generative_ai#large_language_models#machine_translation#multimodal#neural_networks#speaker_diariazation#speaker_recognition#speech_synthesis#speech_translation#tts NVIDIA NeMo is a powerful, easy-to-use platform for building, customizing, and deploying generative AI models like large language models (LLMs), vision language models, and speech AI. It lets you quickly train and fine-tune models using pre-built code and checkpoints, supports the latest model architectures, and works on cloud, data center, or edge environments. NeMo 2.0 is even more flexible and scalable, with Python-based configuration and modular design, making it simple to experiment and scale up. The main benefit is that you can create advanced AI applications faster, with less effort, and at lower cost, while getting high performance and easy deployment options[1][2][3]. https://github.com/NVIDIA/NeMo
Search: #processes
@amazingeo · Post #647 · 02/25/2026, 08:31 PM
🌍 Submarine hydrothermal vents on the ocean floor release superheated water and minerals, fueling unique ecosystems powered by chemical energy instead of sunlight. ✨ #processes⚡#ocean⚡#ecosystems⚡#geography⚡#nature⚡#earth 👉subscribe Amazing Geography 👉more Channels
@amazingeo · Post #39 · 08/13/2025, 12:12 AM
🌍 Earth's crust is in constant motion due to convection currents—slow, swirling movement of hot rock deep below the surface. This drives plate movement, causing earthquakes and forming new land. ✨ #processes⚡#plate⚡#tectonics⚡#geology⚡#geography⚡#nature⚡#earth 👉subscribe Amazing Geography🌍
@djangoproject · Post #430 · 09/02/2017, 03:23 AM
https://docs.python.org/3/library/subprocess.html The #subprocess module allows you to spawn new #processes, connect to their input/output/error pipes, and obtain their return codes. This module intends to replace several older #modules and #functions. #python
@djangoproject · Post #290 · 04/04/2017, 09:36 PM
https://pymotw.com/3/asyncio/executors.html Combining Coroutines with Threads and Processes A lot of existing libraries are not ready to be used with #asyncio natively. They may block, or depend on concurrency features not available through the module. It is still possible to use those libraries in an application based on asyncio by using an #executor from #concurrent.futures to run the code either in a separate thread or a separate process. #Threads The #run_in_executor() method of the event loop takes an executor instance, a regular callable to invoke, and any arguments to be passed to the callable. It returns a Future that can be used to wait for the function to finish its work and return something. If no executor is passed in, a #ThreadPoolExecutor is created. This example explicitly creates an executor to limit the number of worker threads it will have available. #Processes A ProcessPoolExecutor works in much the same way, creating a set of worker #processes instead of threads. Using separate processes requires more system resources, but for computationally-intensive operations it can make sense to run a separate task on each CPU core. #learn