109 lines
3.0 KiB
Markdown
109 lines
3.0 KiB
Markdown
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---
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license: cc-by-nc-sa-4.0
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base_model: Qwen/Qwen2.5-0.5B-Instruct
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tags:
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- task-automation
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- local-llm
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- gguf
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- cpu-inference
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- fine-tuned
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language:
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- en
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library_name: llama-cpp
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pipeline_tag: text-generation
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---
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# ACE 0.5B - Task Automation Model
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Fine-tuned Qwen 0.5B for local task automation. Detects task types and generates execution plans.
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**Code:** [GitHub](https://github.com/ansh0x/ace)
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## Model Description
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ACE is a 0.5B parameter language model fine-tuned for task automation. It can:
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- Classify tasks (atomic, repetitive, clarification needed)
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- Generate CLI commands for file operations
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- Create execution plans with hotkeys
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- Handle repetitive bulk operations
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All inference runs on CPU - no GPU required.
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## Model Files
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| File | Size | Quant | Use Case |
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|------|------|-------|----------|
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| `ace-bf16.gguf` | 940MB | BF16 | **Recommended** - A bit slower inference, but better quality |
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| `ace-q4-k-m.gguf` | 385MB | Q4_K_M | Faster inference |
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## Training Details
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**Base Model:** Qwen/Qwen2-0.5B
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**Method:** LoRA fine-tuning (r=16, alpha=32)
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**Dataset:** ~1000 custom task examples
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**Training:** 500-700 steps, learning_rate=3e-5
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**Quantization:** GGUF Q4_K_M with imatrix
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**Task Types:**
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- Atomic tasks (single operations)
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- Repetitive tasks (bulk processing)
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- Clarification requests (ambiguous inputs)
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**Data Format:**
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```json
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Input: {"task": "...", "directory": [...], "available_hotkeys": [...]}
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Output: {"task_type": "atomic", "output": {"execution_plan": {...}}}
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```
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## Usage
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- Right now the model is a bit unstable and intended for only experimental usages.
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- Refer to the GitHub repo for installation and usage.
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## Limitations
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- Requires explicit file paths (no smart file search)
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- Optimized for Linux commands (Should be able to work on Windows)
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- CPU inference only (3-10 seconds on i3/i5)
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- No visual understanding (text-only)
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- English language only
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## Performance
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**Hardware benchmarks:**
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- Intel i5 (2018+): 3-5 seconds per task
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- Intel i3 (2015+): 5-10 seconds per task
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- Older hardware: 30-90 seconds per task
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## Bias and Ethics
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**Known biases:**
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- Training data focused on common developer workflows
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- Linux command bias (more Linux than Windows examples)
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- English-only (no multilingual support)
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**Ethical considerations:**
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- Model can generate destructive commands (file deletion)
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- Users should review plans before execution
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- No built-in safety checks for harmful operations
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## License
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**CC BY-NC-SA 4.0** (Non-commercial)
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- ✅ Free for personal/research use
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- ❌ Commercial use requires separate license
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- ✅ Must provide attribution
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- ✅ Derivatives must use same license
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**Additional Restriction:**
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Training of AI/ML models using these weights is prohibited without explicit written permission.
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## Contact
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- **Issues:** [GitHub Issues](https://github.com/ansh0x/ace/issues)
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- **Discussions:** [GitHub Discussions](https://github.com/ansh0x/ace/discussions)
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---
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**More info:** [GitHub Repository](https://github.com/ansh0x/ace)
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```
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