Drag and drop your assets (images/videos/audios) to create any video you want using natural language!
It works by asking the model to output a valid FFMPEG and this can be quite complex but most of the time Qwen2.5-Coder-32B gets it right (that thing is a beast). It's an update of an old project made with GPT4 and it was almost impossible to make it work with open models back then (~1.5 years ago), but not anymore, let's go open weights 🚀.
Qwen2.5-72B is now the default HuggingChat model. This model is so good that you must try it! I often get better results on rephrasing with it than Sonnet or GPT-4!!
Maybe like me you have always wanted a super easy way to compare llama3.2-1B vs. llama3.2-3B? or the same model with different temperatures?
Trying and comparing warm Inference API models has never been easier! Just go to https://hf.co/playground, set your token and you're ready to go. We'll keep improving, feedback welcome 😊
Find out by playing Fake Insects 🐞 a Game where you need to identify which insects are fake (AI generated). Good luck & share your best score in the comments!
Together MoA is a really interesting approach based on open source models!
"We introduce Mixture of Agents (MoA), an approach to harness the collective strengths of multiple LLMs to improve state-of-the-art quality. And we provide a reference implementation, Together MoA, which leverages several open-source LLM agents to achieve a score of 65.1% on AlpacaEval 2.0, surpassing prior leader GPT-4o (57.5%)."
Congrats to @alvdansen for one of the nicest SD LoRA ever. It's so sharp and beautiful! Check the model page to try it on your own prompts: alvdansen/BandW-Manga And follow @alvdansen for more 😙
> We introduced a new model designed for the Code generation task. Its test accuracy on the HumanEval base dataset surpasses that of GPT-4 Turbo (April 2024). (90.9% vs 90.2%).