Text Generation
Transformers
English
qwen2
code-generation
python
fine-tuning
Qwen
tools
agent-framework
multi-agent
conversational
Eval Results (legacy)
Instructions to use my-ai-stack/Stack-2-9-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use my-ai-stack/Stack-2-9-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="my-ai-stack/Stack-2-9-finetuned") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("my-ai-stack/Stack-2-9-finetuned") model = AutoModelForCausalLM.from_pretrained("my-ai-stack/Stack-2-9-finetuned") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use my-ai-stack/Stack-2-9-finetuned with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "my-ai-stack/Stack-2-9-finetuned" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "my-ai-stack/Stack-2-9-finetuned", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/my-ai-stack/Stack-2-9-finetuned
- SGLang
How to use my-ai-stack/Stack-2-9-finetuned with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "my-ai-stack/Stack-2-9-finetuned" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "my-ai-stack/Stack-2-9-finetuned", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "my-ai-stack/Stack-2-9-finetuned" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "my-ai-stack/Stack-2-9-finetuned", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use my-ai-stack/Stack-2-9-finetuned with Docker Model Runner:
docker model run hf.co/my-ai-stack/Stack-2-9-finetuned
walidsobhie-code
feat: Add remaining RTMP tools (FileRead, FileWrite, Sleep, AskQuestion, Brief, TaskGet, TeamDelete, MCPTool, Worktree, SyntheticOutput)
5dc5419 | """FileWriteTool - Write content to files for Stack 2.9""" | |
| import os | |
| from datetime import datetime | |
| from pathlib import Path | |
| from .base import BaseTool, ToolResult | |
| from .registry import tool_registry | |
| BACKUP_DIR = Path.home() / ".stack-2.9" / "backups" | |
| class FileWriteTool(BaseTool): | |
| """Write content to a file.""" | |
| name = "file_write" | |
| description = "Write content to a file" | |
| input_schema = { | |
| "type": "object", | |
| "properties": { | |
| "path": {"type": "string", "description": "File path to write"}, | |
| "content": {"type": "string", "description": "Content to write"}, | |
| "append": {"type": "boolean", "default": False, "description": "Append instead of overwrite"}, | |
| "create_backup": {"type": "boolean", "default": True, "description": "Create backup if file exists"} | |
| }, | |
| "required": ["path", "content"] | |
| } | |
| async def execute(self, path: str, content: str, append: bool = False, create_backup: bool = True) -> ToolResult: | |
| """Write file.""" | |
| file_path = Path(path) | |
| # Create parent directories if needed | |
| file_path.parent.mkdir(parents=True, exist_ok=True) | |
| backup_path = None | |
| # Backup existing file | |
| if file_path.exists() and create_backup and not append: | |
| BACKUP_DIR.mkdir(parents=True, exist_ok=True) | |
| timestamp = datetime.now().strftime("%Y%m%d_%H%M%S") | |
| backup_name = f"{file_path.name}.{timestamp}.bak" | |
| backup_path = BACKUP_DIR / backup_name | |
| backup_path.write_text(file_path.read_text()) | |
| # Write content | |
| try: | |
| if append: | |
| existing = file_path.read_text() if file_path.exists() else "" | |
| file_path.write_text(existing + content) | |
| else: | |
| file_path.write_text(content) | |
| except Exception as e: | |
| return ToolResult(success=False, error=f"Cannot write file: {e}") | |
| return ToolResult(success=True, data={ | |
| "path": str(file_path), | |
| "bytes_written": len(content), | |
| "backup": str(backup_path) if backup_path else None, | |
| "mode": "append" if append else "overwrite" | |
| }) | |
| class FileDeleteTool(BaseTool): | |
| """Delete a file.""" | |
| name = "file_delete" | |
| description = "Delete a file" | |
| input_schema = { | |
| "type": "object", | |
| "properties": { | |
| "path": {"type": "string", "description": "File path to delete"}, | |
| "create_backup": {"type": "boolean", "default": True} | |
| }, | |
| "required": ["path"] | |
| } | |
| async def execute(self, path: str, create_backup: bool = True) -> ToolResult: | |
| """Delete file.""" | |
| file_path = Path(path) | |
| if not file_path.exists(): | |
| return ToolResult(success=False, error=f"File not found: {path}") | |
| if not file_path.is_file(): | |
| return ToolResult(success=False, error=f"Not a file: {path}") | |
| backup_path = None | |
| # Backup before delete | |
| if create_backup: | |
| BACKUP_DIR.mkdir(parents=True, exist_ok=True) | |
| timestamp = datetime.now().strftime("%Y%m%d_%H%M%S") | |
| backup_name = f"{file_path.name}.{timestamp}.deleted.bak" | |
| backup_path = BACKUP_DIR / backup_name | |
| backup_path.write_text(file_path.read_text()) | |
| try: | |
| file_path.unlink() | |
| except Exception as e: | |
| return ToolResult(success=False, error=f"Cannot delete file: {e}") | |
| return ToolResult(success=True, data={ | |
| "path": str(file_path), | |
| "deleted": True, | |
| "backup": str(backup_path) if backup_path else None | |
| }) | |
| # Register tools | |
| tool_registry.register(FileWriteTool()) | |
| tool_registry.register(FileDeleteTool()) | |