louisbrulenaudet
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README.md
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| `torch_dtype` | str | The data type utilized in PyTorch operations, such as `float32`. |
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| `max_length` | int | The maximum input length the model can process, specified in tokens. |
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## Citing & Authors
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If you use this dataset in your research, please use the following BibTeX entry.
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| `torch_dtype` | str | The data type utilized in PyTorch operations, such as `float32`. |
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| `max_length` | int | The maximum input length the model can process, specified in tokens. |
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### Organization architecture
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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-poors. A simplified representation might look like this:
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<img src="https://huggingface.co/spaces/HFforLegal/README/resolve/main/assets/HF%20for%20Legal%20architecture%20for%20easy%20deployment.png">
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## Citing & Authors
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If you use this dataset in your research, please use the following BibTeX entry.
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