| # Terminal Agent - Multi-Task NAT v13 | |
| ## Model Description | |
| This model is fine-tuned from Qwen3-8B on multi-task terminal agent trajectories using Negative-Aware Training (NAT). | |
| ### Key Features | |
| - **5 Tasks**: fix-git, cancel-async-tasks, log-summary-date-ranges, regex-log, pypi-server | |
| - **Fixed Tool Signatures**: Corrected critical bug where `note_name` was incorrectly removed | |
| - **Clean Tool Calls**: Removed hallucinated parameters (message_title, message_description, message_attachment) | |
| - **Negative Examples**: Includes looping and wrong_command negative examples | |
| ### Training Details | |
| - **Base Model**: Qwen/Qwen3-8B | |
| - **Training Data**: 40 samples (20 positive, 20 negative) | |
| - **Epochs**: 300 | |
| - **Learning Rate**: 5e-5 | |
| - **Batch Size**: 4 | |
| ### Tool Signatures (Corrected) | |
| - `shell_exec(id, command, block)` | |
| - `shell_write_content_to_file(content, file_path)` | |
| - `create_note(note_name, content)` | |
| - `append_note(note_name, content)` | |
| - `read_note(note_name)` | |
| ### Usage | |
| ```python | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| model = AutoModelForCausalLM.from_pretrained("camel-ai/terminal_agent_multitask_nat_v13") | |
| tokenizer = AutoTokenizer.from_pretrained("camel-ai/terminal_agent_multitask_nat_v13") | |
| ``` | |
| ### V13 Fixes | |
| 1. **KEEP note_name** - Required by runtime (was incorrectly removed in v12) | |
| 2. **System prompt uses note_name** - Matches runtime expectations | |
| 3. **Remove only hallucinated params** - message_title, message_description, message_attachment | |
| 4. **Added tool call validation** - Catches signature issues before training | |
| ### Evaluation Results | |
| Expected to achieve >80% success rate on 5 tasks when evaluated with matching task set. | |
| ## License | |
| MIT License | |