ajibawa-2023/Code-Llama-3-8B

Hugging Face
TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:8kPublished:May 7, 2024License:llama3Architecture:Transformer0.0K Warm

Code-Llama-3-8B by ajibawa-2023 is an 8 billion parameter, fully fine-tuned language model based on Meta's Llama-3-8B architecture, specialized for code generation and mathematical problem-solving. Trained on a refined dataset including Code-290k-ShareGPT and Code-Feedback, it excels at generating code in multiple languages like Python, Java, and C++, often providing detailed explanations. This model also demonstrates strong performance in mathematics, making it suitable for tasks requiring both coding and logical reasoning.

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Model Overview

ajibawa-2023/Code-Llama-3-8B is an 8 billion parameter model, fully fine-tuned from Meta's Llama-3-8B. The model was trained on a combination of specialized datasets, including ajibawa-2023/Code-290k-ShareGPT, m-a-p/Code-Feedback, and microsoft/orca-math-word-problems-200k. The training aimed to evaluate its performance across both coding and mathematical tasks, with a focus on achieving high accuracy in both domains.

Key Capabilities

  • Multi-language Code Generation: Proficient in generating code for various programming languages such as Python, Java, JavaScript, Go, C++, Rust, Ruby, SQL, MySQL, R, Julia, and Haskell.
  • Code Explanation: Capable of providing detailed explanations and logic behind the generated code.
  • Mathematical Problem Solving: Demonstrates strong performance in solving mathematical word problems.
  • ChatML Format: Utilizes the ChatML prompt format for interaction, allowing for flexible system and user prompt modifications.

Training Details

The model was trained for two epochs over 160 hours on 4 x A100 80GB GPUs, using Axolotl and Deepspeed codebase. Quantized versions (GGUF and Exllama v2) are available, thanks to Bartowski.

Good For

  • Developers needing assistance with code generation across a wide array of languages.
  • Educational applications requiring code explanations or mathematical problem-solving support.
  • Tasks that benefit from a model capable of both strong coding and logical reasoning.

Popular Sampler Settings

Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.

temperature
top_p
top_k
frequency_penalty
presence_penalty
repetition_penalty
min_p