| Model Type | |
| Use Cases |
| Areas: | |
| Applications: | | Legal document analysis, Case law review |
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| Primary Use Cases: | | Text generation specific to the legal domain |
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| Considerations: | | Model's accuracy may vary based on input complexity. |
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| Additional Notes | | Supports various precision levels for different hardware efficiencies. |
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| Supported Languages | |
| Training Details |
| Data Sources: | | Open-Orca/OpenOrca, GAIR/lima, WizardLM/WizardLM_evol_instruct_V2_196k, EleutherAI/pile |
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| Methodology: | | Continued pre-training on domain-specific corpora using a reading comprehension approach to enhance prompting ability. |
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| Context Length: | |
| Model Architecture: | | Based on the LLaMA-1 architecture |
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| Input Output |
| Input Format: | | [INST] <> {system_message} <> {prompt} [/INST] |
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| Accepted Modalities: | |
| Output Format: | |
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