Openllm-france

Claire-7B-0.1

OpenLLM-France

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Claire-7B-0.1 is a 7B parameter causal decoder-only language model built by LINAGORA and OpenLLM-France. It was adapted from the Falcon-7b model and fine-tuned on French conversational data. Quantized versions of the model in GGUF format can be found in the TheBloke/Claire-7B-0.1-GGUF repository. Model inputs and outputs Inputs Text prompts for language generation, which can be in the form of open-ended queries, conversations, or instructions. Outputs Continuations of the input text, generated by the model to continue the dialogue or complete the task. Capabilities Claire-7B-0.1 is designed to be adept at generating natural-sounding dialogue and handling conversational interactions. Without further fine-tuning, it is well-suited for tasks like chat-based applications, meeting summarization, and other dialogue-oriented use cases. The model is also capable of generating text on a wide range of topics, though its performance may be more variable outside of its core conversational domain. What can I use it for? The Claire-7B-0.1 model can be used as a foundation for building conversational AI applications, such as chatbots, digital assistants, or dialogue systems. It could also be fine-tuned for tasks like meeting summarization, response generation, and other language-based applications that involve interactive exchanges. The model's French-language focus makes it particularly well-suited for use cases targeting French-speaking audiences. Things to try One interesting aspect of Claire-7B-0.1 is its ability to generate disfluencies and other characteristics of spoken language, which can make the model's outputs feel more natural and human-like in conversational contexts. Developers could experiment with prompting the model to engage in back-and-forth dialogues, and observe how it handles the flow and dynamics of the interaction.

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