🎙️ Léon-v1 : Podcast Research Assistant
📄 Read the full Technical Report on TOAQ
Léon is a fine-tuned model based on Mistral 7B v0.3, optimised to transform complex research documents (LaTeX/PDF) into immersive and accessible podcast scripts.
This v1 version introduces the concept of Temporal Positioning, allowing the generation of structured scripts without redundancies when concatenating long segments.
🚀 Technical Specifications
- Base model: Mistral 7B v0.3 (Unsloth optimised)
- Training method: QLoRA (4-bit quantisation)
- Infrastructure: NVIDIA A100 (40GB VRAM)
- Dataset: 450 pairs of instructions distilled from 41 scientific documents.
- Output format: Plain text with SSML tags
<break time="Xs" />.
🛠️ Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 1e-4 |
| Global Batch Size | 16 (4x4) |
| Steps | 150 |
| Epochs | 6 |
| Optimizer | AdamW 8-bit |
| Precision | Bfloat16 (Native A100 support) |
📊 Performance (Convergence)
The training showed very stable convergence, going from an initial loss of 2.43 to a final loss of 1.06, with an overall minimum of 0.93 (step 149).
- Training Runtime: 455.59 seconds
- Throughput: 5.26 samples/second
- VRAM Peak: 7.6 GB
🎭 Usage (Prompt Engineering)
Léon-v1 uses position tags to structure the narrative:
Introduction (Hook + Presentation)
[Position: START]
Document : [Insert LaTeX text here]
Body of the subject (Technique & Popularisation)
[Position: MIDDLE]
Context : [Summary of the previous segment]
Document : [Next data block]
Conclusion (Outro & Signature)
[Position: END]
⚠️ Limitations & Ethics
Léon is designed for popular science. Although powerful, it can sometimes oversimplify complex mathematical concepts. Always check the output against the source document.
📝 Citation
If you use this template for your research or podcast projects:
@misc{toaq_2026,
author = { TOAQ and Côme Bruneteau },
title = { Leon-7B-Research-Radio-v1 (Revision 70dbad6) },
year = 2026,
url = { https://huggingface.co/TOAQ/Leon-7B-Research-Radio-v1 },
doi = { 10.57967/hf/7866 },
publisher = { Hugging Face }
}
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