A fine-tuned Llama 3.1 8B model specialized for code assistance and conversational programming tasks, trained on curated datasets excluding glaive code assistant data.
A fine-tuned version of Meta's Llama 3.1 8B model, specifically optimized for code assistance and conversational programming tasks. This model was trained on the OH_DCFT_V3 dataset (without glaive code assistant data) and achieves strong performance on code-related queries.
This skill enables you to leverage a specialized code assistant model that can:
When using this model for code assistance tasks:
1. **Model Setup**
- Load the model from HuggingFace: `mlfoundations-dev/OH_DCFT_V3_wo_glaive_code_assistant`
- Use the transformers library with the text-generation pipeline
- Ensure you have sufficient GPU memory (model is 8B parameters)
- Set appropriate generation parameters for code tasks
2. **Input Formatting**
- Frame requests as clear, specific programming questions or tasks
- Provide context about the programming language and framework when relevant
- Include relevant code snippets or error messages for debugging tasks
- Use conversational language - the model is trained for dialogue
3. **Generation Parameters**
- Temperature: 0.2-0.7 (lower for more deterministic code, higher for creative solutions)
- Max tokens: Adjust based on expected output length (512-2048 recommended)
- Top-p: 0.9-0.95 for balanced output
- Stop sequences: Configure based on your use case (e.g., code block delimiters)
4. **Best Practices**
- Break complex tasks into smaller, manageable requests
- Validate generated code before execution
- Iterate on responses by providing feedback or clarifications
- Use the model's conversational capabilities to refine outputs
5. **Performance Considerations**
- Model achieves 0.6738 validation loss on evaluation set
- Trained with constant learning rate schedule and warmup
- Optimized for multi-turn conversations
- Works best with clear, well-structured prompts
**Basic Code Generation:**
```
User: "Write a Python function to calculate the Fibonacci sequence up to n terms"
Model: [Generates complete, documented function]
```
**Debugging Assistance:**
```
User: "I'm getting a KeyError in this dictionary lookup. Here's my code: [code snippet]"
Model: [Analyzes error and suggests fixes]
```
**Code Review:**
```
User: "Can you review this React component and suggest improvements?"
Model: [Provides structured feedback and recommendations]
```
**Multi-turn Conversation:**
```
User: "I need to build a REST API endpoint"
Model: [Asks clarifying questions about framework, database, etc.]
User: "Using FastAPI with PostgreSQL"
Model: [Generates appropriate code with those technologies]
```
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# Download SKILL.md from killerskills.ai/api/skills/llama-31-code-assistant-oh-dcft-v3/raw