Model Description
Mellum-4b-base is JetBrains' first open-source large language model (LLM) optimized for code-related tasks.
Trained on over 4 trillion tokens with a context window of 8192 tokens across multiple programming languages, Mellum-4b-base is tailored specifically for code completion. The model follows a LLaMA-style architecture with 4 billion parameters, making it efficient for both cloud inference (e.g., via vLLM) and local deployment (e.g., using llama.cpp or Ollama).
Mellum was trained using Automatic Mixed Precision (AMP) with bf16 precision. The uploaded version on Hugging Face retains the bf16 format for public use.
Designed for integration into professional developer tooling (e.g., intelligent code suggestions in IDEs), AI-powered coding assistants, and research on code understanding and generation, Mellum is also well-suited for educational applications and fine-tuning experiments.
This release includes a base model, and Python SFT models as well. Models for other languages will be released soon. Keep in mind that base model is not fine-tuned for downstream tasks out-of-the-box, however, it is fully capable of supporting supervised fine-tuning (SFT) and reinforcement learning (RL) for adaptation to specific applications.
Training Data
- Total Training Tokens: ~4.2 trillion tokens
- Corpus: The Stack, StarCoder Training Dataset, The Stack v2, CommitPack, English Wikipedia
Training Details
- Context Window: 8,192 tokens
- Optimization: Standard language modeling objective.
- Hardware: Cluster of 256 x H200 NVIDIA GPUs with Infiniband
- Training Duration: ~20 days
Limitations
- Biases: May reflect biases present in public codebases. For example it will likely produce code which is similar in style to the open-source repositories.
- Security: Code suggestions should not be assumed to be secure or free of vulnerabilities.
Citation
If you use this model, please cite:
@misc{Mellum-4b-base,
title = {Mellum-4b-base},
author = {Pavlichenko, Nikita and Nazarov, Iurii and Dolgov, Ivan and Garanina, Ekaterina and Lasocki, Karol and Reshetnikova, Julia and Boitsov, Sergei and Bondyrev, Ivan and Karaeva, Dariia and Sheptyakov, Maksim and Ustalov, Dmitry and Abramov, Nikita and Kolomyttseva, Olga and Lysaniuk, Kseniia and Zavidnyi, Ilia and Semenkin, Anton and Tankov, Vladislav and Sazanovich, Uladzislau},
year = {2025},
}
Contact
For questions, collaborations and requests reach us out via [email protected]
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