#python#large_language_models#machine_learning_systems#natural_language_processing
Flash Linear Attention (FLA) is a fast, memory-efficient library for advanced linear attention models used in transformers, written in PyTorch and Triton, and compatible with NVIDIA, AMD, and Intel GPUs. It offers many state-of-the-art linear attention models and fused modules that speed up training and reduce memory use. You can easily replace standard attention layers in your models with FLA’s efficient versions, improving training and inference speed, especially for long sequences. FLA supports hybrid models mixing linear and standard attention, and integrates with Hugging Face Transformers for easy use and evaluation. This helps you train and run large language models faster and with less memory, making your AI projects more efficient and scalable.
https://github.com/fla-org/flash-linear-attention
https://docs.python.org/3/library/marshal.html#module-marshal
marshal — Internal Python #object_serialization
This module contains functions that can read and write Python values in a binary format. The format is specific to Python, but independent of machine architecture issues (e.g., you can write a #Python value to a #file on a PC, transport the file to a Sun, and read it back there). Details of the format are undocumented on purpose; it may change between Python versions (although it rarely does).
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Shared by Dimitri
Sharing
Share files and apps on android to other devices using browser
Share files and apps over HTTP.
You need the other device to be connected to the same network. just toggle on the server and scan the QR Code on other device and you're good to go. Files sent from browser to the app can be found in Sharing/ folder in your internal storage. You can always disable uploads in the app settings.
https://github.com/Ammar64/Sharing
Download
https://github.com/Ammar64/Sharing/releases/latest
https://f-droid.org/packages/com.ammar.sharing/
#share#file#Transfer#Android#qr
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#file, #upload, #link, #url, #public, #telegram