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Model: astom-M/matsuo-llm-advanced-phase-imdb1
Source: Original Platform

README.md

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+---
+base_model: Qwen/Qwen2.5-7B-Instruct
+library_name: transformers
+license: apache-2.0
+pipeline_tag: text-generation
+tags:
+- agent
+- sft
+- lora
+- sql
+- household-tasks
+---
+
+# Agent Model - Matsuo LLM Advanced Competition (Phase IMDB1)
+
+Fine-tuned model for DB operation (SQL) and household navigation tasks.
+
+## Model Details
+
+- **Base Model**: [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct)
+- **Training Method**: Supervised Fine-Tuning (SFT) with QLoRA + Instruction Masking
+- **LoRA Configuration**: r=32, alpha=64
+- **Training Data**: 6,750 samples (DB operation + household task trajectories)
+
+## Training Details
+
+### Data Composition
+- **DB operation data**: SQL query generation samples including Spider/BIRD public datasets and Qwen2.5-72B-Instruct distilled samples
+- **Household task data**: Synthetic agent trajectories for navigation and manipulation tasks
+- **Total**: 6,750 samples
+
+### Training Configuration
+- **Epochs**: 1.0
+- **Batch Size**: 4 (effective: 16 with gradient accumulation)
+- **Learning Rate**: 5e-6 (cosine schedule, 5% warmup)
+- **Max Sequence Length**: 4096
+- **Quantization**: 4-bit QLoRA during training, merged to bf16 for inference
+- **Special**: Instruction Masking (loss computed only on assistant response tokens)
+
+## Quick Start
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "astom-M/matsuo-llm-advanced-phase-imdb1"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto")
+
+messages = [
+    {"role": "user", "content": "Your task here..."}
+]
+
+text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+inputs = tokenizer(text, return_tensors="pt").to(model.device)
+
+outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.1)
+response = tokenizer.decode(outputs[0][inputs['input_ids'].shape[1]:], skip_special_tokens=True)
+print(response)
+```
+
+## Framework Versions
+
+- Transformers: 4.57.6
+- PyTorch: 2.10.0
+- PEFT: 0.11.0
+- TRL: 0.24.0
+- Unsloth: 2025.5.8
+
+## License
+
+Apache 2.0 (same as base model Qwen2.5-7B-Instruct)
+
+## Model Development
+
+This model was trained for the Matsuo Lab LLM Advanced Competition 2025:
+- Approved base model: Qwen2.5-7B-Instruct
+- Training method: SFT with QLoRA (r=32, alpha=64) + Instruction Masking
+- Data: Synthetic DB operation + household task trajectories (no ALFWorld or AgentBench data used)
+- Distillation source: Qwen2.5-72B-Instruct (whitelist model)