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  # Claire-7B-0.1
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- **Claire-7B-0.1 is a 7B parameter causal decoder-only model built by [LINAGORA](https://labs.linagora.com/) and [OpenLLM-France](https://github.com/OpenLLM-France)**
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  **adapted from [Falcon-7b](https://huggingface.co/tiiuae/falcon-7b) on French conversational data.**
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  Quantized versions in GGUF format can be found in [TheBloke/Claire-7B-0.1-GGUF](https://huggingface.co/TheBloke/Claire-7B-0.1-GGUF).
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  More evaluation details will be provided in a separate publication.
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  ## License
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  Given that some of the corpora used for training are only available under CC-BY-NC-SA licenses,
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  You can find a variant of this model published under the Apache 2.0 license at [OpenLLM-France/Claire-7B-Apache-0.1](https://huggingface.co/OpenLLM-France/Claire-7B-Apache-0.1).
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  ## Acknowledgements
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  This work was performed using HPC resources from GENCI–IDRIS (Grant 2023-AD011014561).
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- Claire-7B-0.1 was created by members of [LINAGORA](https://labs.linagora.com/) (in alphabetical order): Ismaïl Harrando, Julie Hunter, Jean-Pierre Lorré, Jérôme Louradour, Michel-Marie Maudet, Virgile Rennard, Guokan Shang.
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  Special thanks to partners from the OpenLLM-France community, especially Christophe Cerisara (LORIA), Pierre-Carl Langlais and Anastasia Stasenko (OpSci), and Pierre Colombo, for valuable advice.
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  ## Contact
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  contact@openllm-france.fr
 
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  # Claire-7B-0.1
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+ **Claire-7B-0.1 is a 7B parameter causal decoder-only model built by [LINAGORA](https://labs.linagora.com/) with the support of [OpenLLM-France](https://github.com/OpenLLM-France)**
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  **adapted from [Falcon-7b](https://huggingface.co/tiiuae/falcon-7b) on French conversational data.**
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  Quantized versions in GGUF format can be found in [TheBloke/Claire-7B-0.1-GGUF](https://huggingface.co/TheBloke/Claire-7B-0.1-GGUF).
 
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  More evaluation details will be provided in a separate publication.
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+ ## Variants
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+ Claire-7B-0.1 is finetuned only on French dialogue data, but the following variants are available to evaluate the impact of language mixture on dialogue understanding.
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+ * [Claire-7B-FR-EN-25-75](OpenLLM-France/Claire-7B-FR-EN-25-75-0.1), with 25/75 French-English data split.
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+ * [Claire-7B-FR-EN-50-50](OpenLLM-France/Claire-7B-FR-EN-50-50-0.1), with 50/50 French-English data split.
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+ * [Claire-7B-FR-EN-75-25](OpenLLM-France/Claire-7B-FR-EN-75-25-0.1), with 75/25 French-English data split.
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+ * [Claire-7B](OpenLLM-France/Claire-7B-EN-0.1), with only English data.
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+
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  ## License
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  Given that some of the corpora used for training are only available under CC-BY-NC-SA licenses,
 
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  You can find a variant of this model published under the Apache 2.0 license at [OpenLLM-France/Claire-7B-Apache-0.1](https://huggingface.co/OpenLLM-France/Claire-7B-Apache-0.1).
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+ ## Citation
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+ When using the Claire family of models, please cite the following paper:
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+ Jérôme Louradour, Julie Hunter, Ismaïl Harrando, Guokan Shang, Virgile Rennard & Jean-Pierre Lorré (2024). [Claire: Large Language Models for Spontaneous French Dialogue](https://aclanthology.org/2024.jeptalnrecital-taln.36.pdf). In _Actes de la 31ème Conférence sur le Traitement Automatique des Langues Naturelles, volume 1: articles longs et prises de position_ (pp. 530-548).
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+ ```bibtex
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+ @inproceedings{louradour2024claire,
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+ title={Claire: Large Language Models for Spontaneous French Dialogue},
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+ author={Louradour, J{\'e}r{\^o}me and Hunter, Julie and Harrando, Isma{\"\i}l and Shang, Guokan and Rennard, Virgile and Lorr{\'e}, Jean-Pierre},
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+ booktitle={Actes de la 31{\`e}me Conf{\'e}rence sur le Traitement Automatique des Langues Naturelles, volume 1: articles longs et prises de position},
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+ pages={530--548},
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+ year={2024}
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+ }
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+ ```
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  ## Acknowledgements
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  This work was performed using HPC resources from GENCI–IDRIS (Grant 2023-AD011014561).
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+ Claire-7B-0.1 was created by members of [LINAGORA](https://labs.linagora.com/).
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  Special thanks to partners from the OpenLLM-France community, especially Christophe Cerisara (LORIA), Pierre-Carl Langlais and Anastasia Stasenko (OpSci), and Pierre Colombo, for valuable advice.
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+
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  ## Contact
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  contact@openllm-france.fr