Yhyu13/LMCocktail-10.7B-v1-function-calling
Yhyu13/LMCocktail-10.7B-v1-function-calling is a merged language model based on LMCocktail-10.7B-v1, specifically fine-tuned for function calling capabilities. This model excels at interpreting and generating structured function calls, achieving 9/10 success on the OpenAI function calling cookbook. It is designed for applications requiring robust tool use and integration with external functions, offering improved grounding compared to previous variants.
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LMCocktail-10.7B-v1-function-calling Overview
This model is a specialized variant of the LMCocktail-10.7B-v1 base model, enhanced with function calling capabilities through a fine-tuning LORA. Developed by Yhyu13, it is designed to enable large language models to interact with external tools and APIs by generating structured function calls.
Key Capabilities
- Robust Function Calling: Achieves a high success rate (9/10) on the OpenAI function calling cookbook, indicating strong performance in interpreting and executing function call prompts.
- Improved Grounding: Offers better grounding ability for function calling prompts compared to the developer's previous
ph-2variant. - XML-based Structure: Function calls are wrapped in simple XML tags (
<functioncall>...</functioncall>) for easy identification and extraction, with a similar structure for function responses (<functionresponse>...</functionresponse>). - Integration Ready: Accompanied by a pull request for
text-generation-webuito enable GPT-like function calling, suggesting ease of integration into existing LLM applications.
Good For
- Tool-use Applications: Ideal for scenarios where LLMs need to interact with external tools, databases, or APIs.
- Agentic Workflows: Suitable for building agents that can perform actions by calling specific functions based on user input.
- Drop-in Replacement: Can serve as a replacement for applications (e.g., MemGPT) that require LLMs with reliable function calling abilities.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.