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Model: meftah416/gemma-eppy-270m
Source: Original Platform

README.md

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+---
+base_model: unsloth/gemma-3-270m-it
+library_name: transformers
+tags:
+- text-generation-inference
+- transformers
+- unsloth
+- gemma
+- trl
+- sft
+- energyplus
+- eppy
+- building-simulation
+license: apache-2.0
+language:
+- en
+datasets:
+- self-created
+pipeline_tag: text-generation
+---
+
+# Gemma-3-270M Fine-tuned for EnergyPlus & eppy
+
+**Developed by:** meftah416  
+**Model License:** apache-2.0  
+**Base Model:** [unsloth/gemma-3-270m-it](https://huggingface.co/unsloth/gemma-3-270m-it)
+
+This model was trained **2x faster with [Unsloth](https://github.com/unslothai/unsloth)** ⚡
+
+[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+
+---
+
+## Model Overview
+A specialized Gemma-3-270M model fine-tuned on **EnergyPlus building simulation and eppy Python API** tasks. This model understands and generates text related to building energy simulation, HVAC systems, thermal zones, schedules, and eppy scripting.
+
+### Key Features
+- ✨ Fine-tuned on 2,700 high-quality training examples
+- ✅ Validated on 300 test examples
+- 🚀 2x faster training with Unsloth
+- 💾 Lightweight (270M parameters)
+- 🎯 Domain-specific for EnergyPlus + eppy
+---
+
+## Training Details
+
+| Metric | Value |
+|--------|-------|
+| **Base Model** | unsloth/gemma-3-270m-it |
+| **Training Samples** | 2,700 |
+| **Validation Samples** | 300 |
+| **Total Data** | 3,000 examples |
+| **Data Source** | Self-created |
+| **Domain** | EnergyPlus IDF + eppy Python |
+| **Batch Size** | 2 |
+| **Learning Rate** | 2e-5 |
+| **Optimizer** | adamw_8bit |
+| **Epochs** | 1 |
+| **Max Sequence Length** | 2600 |
+| **Training Framework** | Unsloth + TRL (SFTTrainer) |
+| **Precision** | float16 |
+
+---
+## Model Capabilities
+This model is trained to handle:
+
+### EnergyPlus Tasks
+- Generate EnergyPlus IDF snippets from descriptions
+- Explain EnergyPlus object syntax
+- Create thermal zone definitions
+- Define HVAC system configurations
+- Generate occupancy and schedule objects
+### eppy Tasks
+- Generate eppy Python code for building simulations
+- Explain eppy API usage
+- Create building objects programmatically
+- Manipulate IDF files with eppy
+---
+## Usage
+### Basic Usage
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("meftah416/gemma-eppy-270m")
+tokenizer = AutoTokenizer.from_pretrained("meftah416/gemma-eppy-270m")
+
+# Create messages in correct format
+messages = [
+    {"role": "system", "content": "Set infiltration to 0.4 ACH"},
+    {"role": "user", "content": ""},
+]
+
+# Apply chat template (IMPORTANT!)
+prompt = tokenizer.apply_chat_template(
+    messages,
+    tokenize=False,
+    add_generation_prompt=True
+).removeprefix('<bos>')
+
+# Generate
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs, max_length=2600)
+result = tokenizer.decode(outputs[0])
+```
+# Save to model README on Hub
+---
+## Performance
+- **Inference Speed:** ~50-100 tokens/sec (A10 GPU)
+- **Memory Usage:** 3-4 GB VRAM (float16)
+- **Context Window:** 8192 tokens
+---
+## Limitations
+⚠️ Always validate generated EnergyPlus IDF files before running simulations. Model may occasionally generate incorrect syntax.
+
+---
+## License
+Apache 2.0 License
+
+---
+**Created by:** meftah416