[21] LLM Dataset and generator#129
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…et generator. This dataset is a very basic one to fine-tune the LLM
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Pull request overview
Adds a synthetic multi-turn conversation dataset generator (IT recruiter ↔ candidate) intended for fine-tuning Lucie-7B-Instruct-v1.1, backed by JSON configuration for roles, levels, qualities, and role-specific Q&A.
Changes:
- Introduce a Python script that generates multi-turn recruiter/candidate conversations and writes them to a dataset file.
- Add JSON configuration files for role selection, experience levels, answer “quality”, and role-specific question/answer banks.
Reviewed changes
Copilot reviewed 5 out of 6 changed files in this pull request and generated 4 comments.
Show a summary per file
| File | Description |
|---|---|
| ai/llm-core/datasets/generator/dataset-generator.py | Implements the synthetic conversation generator and dataset writer. |
| ai/llm-core/datasets/generator/config/roles.json | Defines the set of roles to sample when generating conversations. |
| ai/llm-core/datasets/generator/config/levels.json | Defines experience levels used in prompts/responses. |
| ai/llm-core/datasets/generator/config/qualities.json | Defines response quality tiers that control answer content. |
| ai/llm-core/datasets/generator/config/role_data.json | Provides role-specific Q&A templates (with a default fallback). |
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Description
This pull request introduces a dataset generation system for simulating IT recruiter-candidate conversations, aimed at fine-tuning the Lucie-7B-Instruct-v1.1 model. It adds a configurable, multi-role, multi-level, and quality-based synthetic data generator, along with supporting configuration files for roles, levels, qualities, and domain-specific Q&A.
A sample dataset have also been provided.
Linked GitHub Ticket
Closes EpitechPromo2027/G-EIP-600-NAN-6-1-eip-tugdual.de-reviers#21
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