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All Europeans 🇪🇺

LUCIE 🇫🇷 : A French Open-Source Language Model developed by Linagora and the OpenLLM France consortium.

LUCIE is a open-source language model aiming to provide a transparent and sovereign AI solution for Europe. Led by #Linagora and supported by various public and private actors, #LUCIE was publicly released in January 2025.

But it faced significant criticism due to its early development stage. Users were disappointed with its performance, leading to public backlash (similar to ChatGPT's in early days).

The problem is that the project did not clearly communicate LUCIE's early training state, so now when users go to the project website, it greets them with a message explaining the model's current limitations. They encourages users to interact with LUCIE in French and English, focusing on tasks like text generation and summarization, but not complex tasks like mathematics or coding.

To support LUCIE's development, users are invited to test the model and provide feedback.

But because of the public outcry it faced earlier this year, the tool isn't openly available anymore. 😕

Now people have to sign up and ask to participate. If you want to help them train by submitting your questions and giving constructive feedback, you can try!

Website: lucie.chat/en

screenshot of the website written text: "LUCIE — The truly open source AI built on transparency, trust, and efficiency. Lucie the instruct model is no longer available but we work hard to put back online, if you want to be informed when the model will be available, please sign up" On the right, an AI illustration of a blond woman dressed with France's colors (blue, red, white)
pop up in the website that says: "Information notice Lucie is a generative large language model (LLM), meaning that given an input text or "prompt", it will generate a response related to this input. LLMs have to go through numerous phases of training before they are able to respond appropriately and accurately to diverse prompts, and Lucie is at a very early stage in its training, having received just one round of what is known as instruction fine-tuning. This training, while lightweight, gives Lucie the ability to follow basic instructions, such as answering a question or summarizing a text. Its responses may not be reliable yet, but without this additional training, Lucie, when given a prompt, would only be able to generate strings of words that are semantically related to the prompt. Its responses would not have the correct form. In order to move to the next stages of training, we need to collect large amounts of data that come from interactions with human users. In particular, we need feedback on whether an answer provided by Lucie is good or bad or preferable to another. If we get enough high-quality data of this sort, we can use it to teach Lucie to align its responses with the preferences of human users. ... (not enough espace for alt-text, check website)
#opensource#europeanalternatives
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