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I am delighted to announce the publication of my LegalKit, a French labeled dataset built for legal ML training 🤗
I am delighted to announce the publication of my LegalKit, a French labeled dataset built for legal ML training 🤗
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This dataset comprises multiple query-document pairs (+50k) curated for training sentence embedding models within the domain of French law.
This dataset comprises multiple query-document pairs (+50k) curated for training sentence embedding models within the domain of French law.
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The labeling process follows a systematic approach to ensure consistency and relevance:
The labeling process follows a systematic approach to ensure consistency and relevance:
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- Initial Query Generation: Three instances of the LLaMA-3-70B model independently generate three different queries based on the same document.
- Initial Query Generation: Three instances of the LLaMA-3-70B model independently generate three different queries based on the same document.
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- Selection of Optimal Query: A fourth instance of the LLaMA-3-70B model, using a dedicated selection prompt, evaluates the generated queries and selects the most suitable one.
- Selection of Optimal Query: A fourth instance of the LLaMA-3-70B model, using a dedicated selection prompt, evaluates the generated queries and selects the most suitable one.
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- Final Label Assignment: The chosen query is used to label the document, aiming to ensure that the label accurately reflects the content and context of the original text.
- Final Label Assignment: The chosen query is used to label the document, aiming to ensure that the label accurately reflects the content and context of the original text.
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Dataset: 
Dataset: 
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https://huggingface.co/datasets/louisbrulenaudet/legalkit
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louisbrulenaudet/legalkit
https://huggingface.co/datasets/louisbrulenaudet/legalkit
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Stay tuned for further updates and release information 🔥
Stay tuned for further updates and release information 🔥
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@clem
clem
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, if we can create an "HF for Legal" organization, similar to what exists for journalists, I am available!
, if we can create an "HF for Legal" organization, similar to what exists for journalists, I am available!
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Note : My special thanks to 
Note : My special thanks to 
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@alvdansen
alvdansen
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 for their illustration models ❤️
 for their illustration models ❤️
I am delighted to announce the publication of my LegalKit, a French labeled dataset built for legal ML training 🤗

This dataset comprises multiple query-document pairs (+50k) curated for training sentence embedding models within the domain of French law.

The labeling process follows a systematic approach to ensure consistency and relevance:
- Initial Query Generation: Three instances of the LLaMA-3-70B model independently generate three different queries based on the same document.
- Selection of Optimal Query: A fourth instance of the LLaMA-3-70B model, using a dedicated selection prompt, evaluates the generated queries and selects the most suitable one.
- Final Label Assignment: The chosen query is used to label the document, aiming to ensure that the label accurately reflects the content and context of the original text.

Dataset: https://huggingface.co/datasets/louisbrulenaudet/legalkit

Stay tuned for further updates and release information 🔥

@clem, if we can create an "HF for Legal" organization, similar to what exists for journalists, I am available!

Note : My special thanks to @alvdansen for their illustration models ❤️
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fffiloni ZeroWw Ramikan-BR ssatz davanstrien clem osanseviero baconnier
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Ramikan-BR clem umseeker baconnier louisbrulenaudet LeroyDyer sbrandeis
🚀
KvrParaskevi Ramikan-BR antoinejeannot
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Ramikan-BR
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Ramikan-BR
https://cdn-avatars.huggingface.co/v1/production/uploads/635dd6cd4fabde0df74aeae6/23c0uEOr7RWDtSLDBzkPD.png
araminta_k
alvdansen
user
https://cdn-avatars.huggingface.co/v1/production/uploads/1583857146757-5e67bdd61009063689407479.jpeg
Clem 🤗
clem
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