Welcome to HF for Legal, a community dedicated to breaking down the opacity of language models for legal professionals. Our mission is to empower legal practitioners, scholars, and researchers with the knowledge and tools they need to navigate the complex world of AI in the legal domain.
At HF for Legal, we aim to:
- Demystify AI language models for the legal community
- Share curated resources, including specialized legal models, datasets, and tools
- Foster collaboration on projects that enhance legal research and practice through AI
- Provide a platform for discussing ethical implications and best practices of AI in law
- Offer tutorials and workshops on leveraging AI technologies in legal work
By bringing together legal experts, AI researchers, and technology enthusiasts, we strive to create an open ecosystem where legal professionals can easily access, understand, and utilize AI models tailored to their needs. Whether you're a practicing attorney, a legal scholar, or a technologist interested in legal applications of AI, HF for Legal is your hub for exploration, learning, and innovation in the evolving landscape of AI-assisted legal practice.
Join us in our mission to make AI more accessible and understandable for the legal world, ensuring that the power of language models can be harnessed effectively and ethically in the pursuit of justice.
🤗 Assistants
Assistants are a great way to configure models to perform specific tasks. You can find an example with the French law based on legal codes and cases:
The prompts behind them are public. Feel free to tailor them to your needs. Also, share your ideas for other Assistants in the Community tab!
hf-for-legal, A Community Package for Legal Applications
You can now download the community package to format your splits and upload in an easier manner your data to the hub.
pip3 install hf-for-legal
Find the documentation of the package on PyPi: https://pypi.org/project/hf-for-legal/
Organization architecture
In order to simplify the deployment of the organization's various tools, we propose a simple architecture in which datasets containing the various legal and contractual texts are doubled by datasets containing embeddings for different models, to enable simplified index creation for Spaces initialization and the provision of vector data for the GPU-poor. A simplified representation might look like this:
Community Discord
You can now join, communicate and share on the HF for Legal community server on Discord.
Link to the server: discord.gg/adwsfUUhw8
This server will simplify communication between members of the organization and generate synergies around the various projects in the three areas of interactive applications, databases and models.
An example of a project soon to be published: a duplication of the Laws database, but this time containing embeddings already calculated for different models, to enable simplified integration within Spaces (RAG chatbot ?) and save deployment costs for users wishing to use these technologies for their professional and personal projects.