Etherll/Mellum-4b-sft-rust is a large language model (LLM) fine-tuned specifically for Rust code Fill-in-the-Middle (FIM) tasks. It is built upon JetBrains/Mellum-4b-base model.
This model has been fine-tuned on the Etherll/CodeFIM-Rust-Mellum dataset, which comprises approximately 57,000 Rust-specific FIM examples, to enhance its proficiency in completing Rust code snippets accurately and contextually.
This model leverages the LLaMA-style architecture of Mellum-4b-base (4 billion parameters) and its extensive pre-training on over 4 trillion tokens. The fine-tuning process focused on adapting the model to the nuances of Rust syntax and common coding patterns for FIM tasks.
Key Features:
Specialized for Rust: Optimized for Fill-in-the-Middle tasks in Rust.
Based on Mellum-4b-base: Benefits from JetBrains' robust base model.
Efficient: Suitable for both cloud and local deployment.
IDE Integration Ready: Designed for use in developer tooling, and works particularly well with Continue.dev for an enhanced coding assistant experience.
Fine-tuning Data
Dataset:Etherll/CodeFIM-Rust-Mellum
Size: ~57,000 rows
Focus: Rust code Fill-in-the-Middle
FIM Format
This model is trained to recognize a specific format for Fill-in-the-Middle tasks. When providing input for FIM, please use the following structure:
A GGUF version is available at Etherll/Mellum-4b-sft-rust-GGUF.
This format is suitable for local inference on CPU (and GPU with appropriate llama.cpp/Ollama builds) using tools like:
