| --- |
| license: other |
| license_name: lfm1.0 |
| license_link: https://huggingface.co/LiquidAI/LFM2-350M/blob/main/LICENSE |
| metrics: |
| - magic judge |
| base_model: |
| - LiquidAI/LFM2-700M |
| tags: |
| - lmstudio |
| - madlabOSS |
| - magic judge |
| --- |
| |
| # LMS Guide 700m |
|
|
| ## 🧠 Overview |
| The **LMS Guide 700m** is part of the **MadlabOSS LM Studio Guide** family — a lineup of small, efficient, and highly aligned assistant models trained specifically to provide deterministic, hallucination‑resistant guidance for LM Studio users. |
|
|
| This model is trained on a curated dataset of LM Studio–specific instructions, workflows, troubleshooting steps, and conceptual explanations. |
|
|
| --- |
|
|
| ## 🚀 Intended Use |
| This model is optimized for: |
|
|
| - LM Studio onboarding |
| - workflow explanations |
| - feature descriptions |
| - troubleshooting guidance |
| - plugin/server integration help |
| - safe, deterministic assistant behavior |
|
|
| It is **not** intended as a general‑purpose chatbot. |
|
|
| --- |
|
|
| ## 🧩 Model Details |
|
|
| **Base Model:** LFM2‑700m |
| **Parameter Count:** 700 Million |
| **Training Type:** Supervised fine‑tuning |
| **Sequence Length:** 320 |
| **Precision:** FP16 |
| **Framework:** PyTorch / Transformers |
|
|
| --- |
|
|
| ## 📦 Training Data |
| The model was trained on: |
|
|
| - **6,000+ LM Studio–specific instruction/response pairs** |
| - Clean, domain‑specific, ontology‑consistent data |
| - Minor general‑purpose conversational data |
| - No web‑scraped content |
| - Full LM Studio Documentation |
|
|
| A 36k+ expanded dataset is planned for v2.0. |
|
|
| --- |
|
|
| ## 🏋️ Training Procedure |
|
|
| ### **Hyperparameters** |
| - Epochs: 6 |
| - Batch size: 4 |
| - Learning rate: cosine schedule, peak ~4e‑5 |
| - Optimizer: AdamW |
| - Gradient clipping: 1.0 |
| - Gradient accumulation: 1 |
|
|
| ### **Hardware** |
| Training was performed on: |
|
|
| - RTX 6000 Ada (96GB) (1.2b + 2.6b) |
| - Dual RTX 3090 (Magic Judge) |
| - RTX 3070 (for 0.35B + 0.7b) |
|
|
| --- |
|
|
| ## 📊 Evaluation |
|
|
| ### **Judge Score** |
| Semantic correctness, ontology adherence, and hallucination resistance. |
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|
|
|
| ### **Qualitative Behavior** |
| - Strong adherence to LM Studio terminology |
| - Low hallucination rate |
| - Deterministic, predictable responses |
| - Not optimized for open‑domain reasoning |
|
|
| --- |
|
|
| ## 🔒 Safety |
| This model is trained exclusively on LM Studio–specific content. |
| It avoids hallucinating non‑existent LM Studio features and adheres to a strict ontology. |
|
|
| It is **not** designed for: |
|
|
| - political content |
| - medical advice |
| - legal advice |
| - general‑purpose conversation |
|
|
| --- |
|
|
| ## ⚠️ Limitations |
| - Not a general assistant |
| - Not trained for coding, math, or open‑domain reasoning |
| - May refuse tasks outside LM Studio scope |
| - Static accuracy metrics underestimate real performance |
|
|
| --- |
