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A 4B parameter agent foundation model specialized in long-horizon tasks with sustained deep exploration capabilities. Performs multi-source cross-validation, dynamic search strategies, and real-time verification across complex benchmarks like GAIA, HLE, and BrowserComp.
Quantized GGUF format model specialized in mathematical reasoning and problem-solving, optimized for efficient local inference with llama.cpp
Expert assistant for working with the personalUtils codebase - a Python toolkit featuring GPT-powered chat, 4 specialized AI agents, 12 utility tools, and agentic workflows.
Comprehensive Aider AI coding assistant configuration template with settings for models, API keys, git integration, output customization, and workflow automation. Covers all available configuration options for optimal Aider setup.
Expert guidance for building mobile apps with TypeScript, React Native, Expo, and modern UI patterns following best practices for performance, accessibility, and security.
A specialized Llama 3 8B model fine-tuned for function calling and tool use, optimized for generating structured API calls and handling multi-turn conversations with tool integration.
Fine-tuned Turkish Llama 8B model that performs function calling tasks in Turkish using JSON schema definitions
Fine-tuned Llama 2 7B model for function calling using OpenAI-compatible metadata format. Suitable for commercial use with multi-turn conversation support.
A 20B parameter model specialized in function calling capabilities, supporting nested calls, function chaining, parallel functions, and parameter detection across multiple quantization formats (GGUF).
A 1.2B parameter liquid neural network model specialized in function calling and tool use, optimized for conversational AI agents that need to interact with external tools and APIs.
Deploy a lightweight 135M parameter model for function calling tasks with 92% structural validity. Perfect for edge devices, mobile apps, IoT systems, and embedded applications requiring structured function invocation without cloud dependency.
A 1.2B parameter Liquid Neural Network model specialized for converting natural language queries into structured JSON function calls. Runs efficiently on low-resource hardware while achieving 97% syntax reliability.
Fine-tuned Llama 3.1 8B model specialized for function calling tasks, trained on the xlam-function-calling-60k dataset using reward-model-filtered data.
Quantized GGUF version of DeepSeek Coder 6.7B fine-tuned for chat and function calling with OpenAI-compatible syntax. Multiple quantization levels available from 2.36GB to 6.67GB.
Use IBM's Granite-20B-FunctionCalling model to enable multi-task function calling capabilities including nested functions, function chaining, parallel execution, and intelligent parameter detection for AI agents.
A finetuned CodeLlama-7b model specialized in code completion, generation, refactoring, and documentation across Python, C++, Java, and JavaScript.
A compact 1.2B parameter liquid neural network model specialized in function calling and tool use, optimized for conversational AI applications with structured function execution capabilities.
A dynamic multi-expert LLM system that routes questions to specialized models (programming, biology, mathematics) using keyword matching and a director model for optimal domain-specific responses.
Development assistant for gatsby-theme-chronogrove, a Gatsby theme monorepo powering a personal website with social dashboard widgets. Helps with decoupling personal content, widget development, testing, and theme configuration.
A specialized AI agent model focused on security, safety, and agent-based tasks. Based on Llama 3.1 8B architecture, fine-tuned for security analysis and conversational safety assessment. Available in multiple GGUF quantization formats optimized for different hardware constraints.