Search Results for "3.1"

The 'llama-recipes' repository is a companion to the Meta Llama models. We support the latest version, Llama 3.1, in this repository. The goal is to provide a scalable library for fine-tuning Meta Llama models, along with some example scripts and notebooks to quickly get started with using the models in a variety of use-cases, including fine-tuning for domain adaptation and building LLM-based applications with Llama and other tools in the LLM ecosystem.

...The project provides full, dev, and fast model variants with different inference step counts. It supports direct Python inference scripts, an interactive Gradio demo, and integration through the Hugging Face Diffusers library. The model uses a Llama 3.1 text encoder path and requires the proper Hugging Face access setup for automatic downloads. It is useful for researchers, developers, and creative AI builders who want an open text-to-image model with strong benchmark performance and multiple deployment options.

...It transcribes top performers locally with Whisper, extracts the hook and structure with AI, then assembles original videos — AI-written scripts, AI voiceover (Gemini 3.1 Flash TTS, free Edge TTS, or a voice you cloned on-device), word-by-word animated captions and background music — or generates AI video clips with Sora 2 Pro, Veo 3.1, Seedance and Wan. Newer modes turn a prompt into motion-graphics animations (kinetic typography rendered from HTML) and turn any website URL into a polished promo video.

...All you need is a text file ending in the tittse extension with 4 header lines including the TITTSE language code (see documentation), the 'base' file name for the audio files TITTSE creates, voice gender (girl or boy), offset (file numbers added to base file name start at this number). After those first four lines, every paragraph is created as a single audio file. Install_TITTSE.sh is a Bash script that installs Python 3.1 and all needed dependencies in a virtual environment on your Linux system. All you need for installation is a Linux system and the TITTSE.zip file. Extract the zip then run Install_TITTSE.sh. That easy! Splash and Icon Artwork created by Bridgett Marlow and released under CC0 license. TITTSE by John Marlow and released under GNU GPL 3.0 or greater. ...

Sockeye is an open-source sequence-to-sequence framework for Neural Machine Translation built on PyTorch. It implements distributed training and optimized inference for state-of-the-art models, powering Amazon Translate and other MT applications. For a quickstart guide to training a standard NMT model on any size of data, see the WMT 2014 English-German tutorial. If you are interested in collaborating or have any questions, please submit a pull request or issue. You can also send questions...