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Introducing IGEL, an instruction-tuned German large Language Model! 🇩🇪🤯
IGEL is an LLM designed for German language understanding tasks, including sentiment analysis, language translation, and question answering. The first version of IGEL is built on top of BigScience BLOOM and adapted to German. 🔥
News & Announcements 📣
Together released a new version of their chatGPT-NeoX 20B model with higher quality by fine-tuning on user feedback.
VALL-E X, for cross-lingual speech synthesis, got released by Microsoft
The University of Berkley released Koala-13B! An open-source chatbot trained by fine-tuning LLaMA on web dialogue! 50% of responses are similar to ChatGPT.
Tutorials & Demos 📝
Regis from HF created a tutorial on how to deploy BLOOMZ (176B) on Habana Gaudi2, outperforming NVIDIA A100s.
Langchain created a template on how to create AIPlugins for LLMs.
Reads & Papers 📚
Samuel R. Bowman surveys a paper about Eight Things to Know about Large Language Models.
LLMs can Iteratively Self-Refine themselves.
Microsoft shows that using GPT-4 for data generation can help improve smaller models.
Bloomberg released a paper on their experiences training a 50B GPT model specialized on financial data.
HuggingGPT from Microsoft presents a new method to use LLMs as “routers” for requests to smaller fine-tuned LMs.
See you next week 👋🏻👋🏻