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", device_map="auto") 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 Settings
- 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
| """ | |
| Debugging Assistant Module | |
| Provides debugging assistance and error analysis. | |
| """ | |
| from typing import Dict, List, Optional, Any, Tuple | |
| import re | |
| class DebuggingAssistant: | |
| """Helps debug code and analyze errors.""" | |
| # Common error patterns and their explanations | |
| ERROR_PATTERNS = { | |
| "python": { | |
| "SyntaxError": { | |
| "description": "Python syntax is invalid", | |
| "common_causes": [ | |
| "Missing colon after if/for/while/function definitions", | |
| "Mismatched parentheses or brackets", | |
| "Incorrect indentation", | |
| "Using Python 2 syntax in Python 3", | |
| ], | |
| }, | |
| "NameError": { | |
| "description": "A variable or function name is not defined", | |
| "common_causes": [ | |
| "Typo in variable name", | |
| "Variable used before assignment", | |
| "Import statement missing", | |
| "Scope issue - variable not accessible", | |
| ], | |
| }, | |
| "TypeError": { | |
| "description": "Operation applied to wrong type", | |
| "common_causes": [ | |
| "Trying to concatenate incompatible types", | |
| "Calling a non-callable as a function", | |
| "Passing wrong number of arguments", | |
| "Operation not supported for type", | |
| ], | |
| }, | |
| "IndexError": { | |
| "description": "List index out of range", | |
| "common_causes": [ | |
| "Accessing index that doesn't exist", | |
| "Empty list access", | |
| "Off-by-one error", | |
| ], | |
| }, | |
| "KeyError": { | |
| "description": "Dictionary key not found", | |
| "common_causes": [ | |
| "Accessing non-existent key", | |
| "Typo in key name", | |
| "Case sensitivity issue", | |
| ], | |
| }, | |
| "AttributeError": { | |
| "description": "Object has no attribute", | |
| "common_causes": [ | |
| "Typo in attribute name", | |
| "Object is None when trying to access attribute", | |
| "Wrong type for this operation", | |
| ], | |
| }, | |
| "ImportError": { | |
| "description": "Cannot import module", | |
| "common_causes": [ | |
| "Module not installed", | |
| "Circular import", | |
| "Module name typo", | |
| "Missing __init__.py in package", | |
| ], | |
| }, | |
| "ZeroDivisionError": { | |
| "description": "Division by zero", | |
| "common_causes": [ | |
| "Dividing by variable that could be zero", | |
| "Modulo by zero", | |
| ], | |
| }, | |
| "ValueError": { | |
| "description": "Value is inappropriate", | |
| "common_causes": [ | |
| "Invalid argument to function", | |
| "Conversion failed (e.g., int('abc'))", | |
| "Empty sequence in function expecting content", | |
| ], | |
| }, | |
| "IndentationError": { | |
| "description": "Incorrect indentation", | |
| "common_causes": [ | |
| "Mixing tabs and spaces", | |
| "Inconsistent indentation levels", | |
| "Code not aligned properly", | |
| ], | |
| }, | |
| }, | |
| "javascript": { | |
| "ReferenceError": { | |
| "description": "Variable not defined", | |
| "common_causes": [ | |
| "Typo in variable name", | |
| "Using let/const before declaration", | |
| ], | |
| }, | |
| "TypeError": { | |
| "description": "Type operation failed", | |
| "common_causes": [ | |
| "Calling non-function", | |
| "Cannot read property of undefined/null", | |
| ], | |
| }, | |
| "SyntaxError": { | |
| "description": "Invalid syntax", | |
| "common_causes": [ | |
| "Missing closing bracket/parenthesis", | |
| "Invalid string quotes", | |
| ], | |
| }, | |
| }, | |
| } | |
| def __init__(self): | |
| """Initialize debugging assistant.""" | |
| pass | |
| def analyze_error( | |
| self, | |
| error_message: str, | |
| language: str = "python", | |
| ) -> Dict[str, Any]: | |
| """ | |
| Analyze an error message and provide debugging help. | |
| Args: | |
| error_message: The error message | |
| language: Programming language | |
| Returns: | |
| Dictionary with error analysis and suggestions | |
| """ | |
| # Extract error type | |
| error_type = self._extract_error_type(error_message, language) | |
| # Get error info | |
| error_info = self.ERROR_PATTERNS.get(language, {}).get(error_type, { | |
| "description": "Unknown error", | |
| "common_causes": ["Check the error message for clues"], | |
| }) | |
| # Generate debugging steps | |
| steps = self._generate_debug_steps(error_type, error_message, language) | |
| # Suggest fixes | |
| fixes = self._suggest_fixes(error_type, error_message, language) | |
| return { | |
| "error_type": error_type, | |
| "description": error_info["description"], | |
| "common_causes": error_info["common_causes"], | |
| "debug_steps": steps, | |
| "suggested_fixes": fixes, | |
| } | |
| def _extract_error_type(self, error_message: str, language: str) -> str: | |
| """Extract error type from error message.""" | |
| # Look for common error patterns | |
| patterns = { | |
| "python": [ | |
| (r"(\w+Error):", 1), | |
| (r"(\w+Exception):", 1), | |
| ], | |
| "javascript": [ | |
| (r"(\w+Error):", 1), | |
| (r"(\w+TypeError):", 1), | |
| ], | |
| } | |
| for pattern, group in patterns.get(language, []): | |
| match = re.search(pattern, error_message) | |
| if match: | |
| return match.group(group) | |
| return "UnknownError" | |
| def _generate_debug_steps( | |
| self, | |
| error_type: str, | |
| error_message: str, | |
| language: str, | |
| ) -> List[str]: | |
| """Generate debugging steps for the error.""" | |
| steps = [ | |
| "1. Read the error message carefully - it tells you what went wrong", | |
| "2. Check the line number in the traceback", | |
| "3. Look at the context around that line", | |
| ] | |
| if error_type == "NameError": | |
| steps.extend([ | |
| "4. Check if the variable is spelled correctly", | |
| "5. Verify the variable is defined before use", | |
| "6. Check if you need to import the module", | |
| ]) | |
| elif error_type == "TypeError": | |
| steps.extend([ | |
| "4. Check the types of variables involved", | |
| "5. Use print() or logging to debug values", | |
| "6. Use type() to check variable types", | |
| ]) | |
| elif error_type == "IndexError": | |
| steps.extend([ | |
| "4. Check the list length before accessing", | |
| "5. Consider using try/except for bounds", | |
| "6. Check if the list is empty", | |
| ]) | |
| elif error_type == "ImportError": | |
| steps.extend([ | |
| "4. Verify the package is installed (pip list / npm list)", | |
| "5. Check the package name is correct", | |
| "6. Try reinstalling the package", | |
| ]) | |
| return steps | |
| def _suggest_fixes( | |
| self, | |
| error_type: str, | |
| error_message: str, | |
| language: str, | |
| ) -> List[str]: | |
| """Suggest fixes for the error.""" | |
| fixes = [] | |
| if error_type == "NameError": | |
| fixes.append("Check spelling of all variable/function names") | |
| fixes.append("Ensure variable is defined before use") | |
| fixes.append("Add necessary import statements") | |
| elif error_type == "TypeError": | |
| fixes.append("Convert types explicitly if needed") | |
| fixes.append("Check you're using the right operators") | |
| fixes.append("Verify function accepts the arguments given") | |
| elif error_type == "IndexError": | |
| fixes.append("Add bounds checking before access") | |
| fixes.append("Use .get() for dictionaries") | |
| fixes.append("Check if list is empty first") | |
| elif error_type == "SyntaxError": | |
| fixes.append("Check for missing colons, brackets, quotes") | |
| fixes.append("Verify indentation is consistent") | |
| fixes.append("Run a linter to find issues") | |
| return fixes | |
| def analyze_traceback(self, traceback: str) -> Dict[str, Any]: | |
| """ | |
| Analyze a full traceback. | |
| Args: | |
| traceback: The full error traceback | |
| Returns: | |
| Dictionary with traceback analysis | |
| """ | |
| lines = traceback.split('\n') | |
| # Extract file and line numbers | |
| file_lines = [] | |
| for line in lines: | |
| if 'File "' in line or 'line ' in line: | |
| file_lines.append(line.strip()) | |
| # Get the main error | |
| error_line = "" | |
| for line in lines: | |
| if 'Error:' in line or 'Exception:' in line: | |
| error_line = line.strip() | |
| break | |
| return { | |
| "files_involved": file_lines, | |
| "main_error": error_line, | |
| "frames": len([l for l in lines if 'File "' in l]), | |
| } | |
| def generate_debug_code( | |
| self, | |
| error_type: str, | |
| code_snippet: str, | |
| ) -> str: | |
| """Generate debugging code for the error.""" | |
| debug_templates = { | |
| "NameError": f"""# Debug NameError | |
| # Add debugging print statements | |
| print(f"Variable value: {{variable_name}}") | |
| # Check if defined | |
| try: | |
| result = {code_snippet} | |
| except NameError as e: | |
| print(f"NameError: {{e}}")""", | |
| "TypeError": f"""# Debug TypeError | |
| # Add type checking | |
| print(f"Type of variable: {{type(variable_name)}}") | |
| # Add type hints for clarity | |
| def debug_function(variable_name): | |
| print(f"Value: {{variable_name}}, Type: {{type(variable_name)}}") | |
| return variable_name""", | |
| "IndexError": f"""# Debug IndexError | |
| # Add bounds checking | |
| my_list = [] | |
| if len(my_list) > 0: | |
| print(f"List has {{len(my_list)}} items") | |
| # Access with safety | |
| result = my_list[0] if my_list else None""", | |
| "default": """# General debug approach | |
| import traceback | |
| try: | |
| # Your code here | |
| pass | |
| except Exception as e: | |
| print(f"Error: {{e}}") | |
| traceback.print_exc() | |
| # Add your debugging here""" | |
| } | |
| return debug_templates.get(error_type, debug_templates["default"]) | |
| def suggest_logging(self, code: str) -> str: | |
| """Suggest where to add logging statements.""" | |
| suggestions = [] | |
| # Suggest logging for function calls | |
| functions = re.findall(r'def\s+(\w+)\s*\(', code) | |
| for func in functions[:3]: # Limit to 3 | |
| suggestions.append(f"Add logging at start/end of function '{func}()'") | |
| # Suggest logging for error handling | |
| if "except" in code: | |
| suggestions.append("Add logging in exception handlers") | |
| # Suggest logging for loops | |
| if "for " in code: | |
| suggestions.append("Add logging in loops to track iterations") | |
| return suggestions if suggestions else ["Code looks simple, minimal logging needed"] | |
| def __repr__(self) -> str: | |
| return "DebuggingAssistant()" |