Archi-medes/LabGuide_Preview

LabGuide Preview Model

Model Summary

The LabGuide Preview Model is a demonstration release built entirely with Madlab, using its synthetic dataset generator and training workflow.
It is based on LiquidAI/LFM2-700M, adapted to showcase Madlab’s end-to-end capabilities for dataset creation, model training, and assistant deployment.

This model illustrates how applications can leverage Madlab to train their own assistants in a reproducible and accessible way.
It is not intended for production use, but rather as a preview for contributors, collaborators, and community feedback.

---

Training Data

• Source: Synthetic dataset generated entirely with Madlab’s dataset generator.
• Purpose: Designed to demonstrate Madlab’s ability to produce structured, reproducible training data.
• Scope: Preview-scale dataset, not representative of real-world or production-ready corpora.

---

Training Process

• Framework: Madlab training pipeline.
• Base Model: LiquidAI/LFM2-700M.
• Workflow: Synthetic dataset generation → Madlab training loop → Magic Judge Evaluation → Preview model release.
• Objective: Demonstrate Madlab’s integrated workflow for building application-specific assistants.

---

Intended Uses

• Contributor onboarding and workflow validation.
• Demonstration of Madlab’s synthetic dataset generator and training pipeline.
• Benchmarking and experimentation in controlled preview settings.

---

Limitations

• Demo-only: Not suitable for production or deployment in real-world applications.
• Synthetic data: Training data is fully synthetic and may not reflect natural language distributions.
• Preview scale: Model performance is illustrative, not optimized for accuracy or robustness.

---

Ethical Considerations

• This model is provided for demonstration and educational purposes.
• It should not be used in applications where accuracy, safety, or reliability are critical.
• Contributors are encouraged to treat outputs as illustrative examples only.

---

Acknowledgements

• Base model: LiquidAI/LFM2-700M.
• Built and trained with Madlab.