harshism1/codellama-leetcode-finetuned

TEXT GENERATIONConcurrency Cost:1Model Size:7BQuant:FP8Ctx Length:4kArchitecture:Transformer0.0K Cold

The harshism1/codellama-leetcode-finetuned model is a 7 billion parameter CodeLlama-based instruction-tuned language model developed by harshism1. Fine-tuned on the LeetCode dataset, this model specializes in generating Python solutions for LeetCode-style programming problems. It offers a 4096-token context length and is optimized for code generation tasks, available in both Transformers-compatible and GGUF formats.

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Model Overview

The harshism1/codellama-leetcode-finetuned model is a specialized 7 billion parameter language model built upon the codellama/CodeLlama-7b-Instruct-hf architecture. Developed by harshism1, this model has undergone instruction-tuning specifically using the greengerong/leetcode dataset.

Key Capabilities

  • LeetCode Problem Solving: The primary capability of this model is to generate Python solutions for programming problems presented in a LeetCode-style format.
  • Code Generation: It excels at understanding problem descriptions and producing functional code snippets.
  • Instruction-Tuned: The model is fine-tuned to follow instructions for solving coding challenges, making it suitable for automated problem-solving or developer assistance.

Technical Details

  • Base Model: CodeLlama-7b-Instruct-hf
  • Fine-tuning Dataset: greengerong/leetcode
  • Context Length: Supports a context window of 4096 tokens.
  • Model Formats: Available in:
    • Transformers-compatible (.safetensors): For seamless integration with the Hugging Face Transformers library.
    • GGUF (.gguf): Optimized for efficient inference with llama.cpp and related tools like llama-cpp-python and llama-server.

Use Cases

This model is particularly well-suited for:

  • Automated Code Solution Generation: Generating Python code for competitive programming or technical interview preparation.
  • Developer Tools: Integrating into IDEs or coding platforms to provide solution suggestions.
  • Educational Purposes: Assisting learners in understanding different approaches to LeetCode problems.

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