starcoderbase-1b-sft

Maintained By
abacaj

StarCoderBase-1B-SFT

PropertyValue
Authorabacaj
Model TypeText Generation (Code)
FrameworkPyTorch
Training Dataevol-codealpaca-v1
LanguageEnglish

What is starcoderbase-1b-sft?

StarCoderBase-1B-SFT is a specialized code generation model that has been fine-tuned on the evol-codealpaca dataset. This model represents a significant advancement in code-generation capabilities, demonstrating strong performance on standard benchmarks with a 39% pass@1 rate on HumanEval and 31.74% on MBPP.

Implementation Details

The model is implemented using the PyTorch framework and leverages the Transformers architecture. It includes a comprehensive inference pipeline that supports features like temperature control and top-p sampling for generated outputs. The model can be easily deployed using the provided implementation code, which includes proper token handling and GPU acceleration.

  • Built on the gpt_bigcode architecture
  • Supports text-generation-inference endpoints
  • Includes temperature and top-p sampling controls
  • Maximum new token generation of 512 tokens

Core Capabilities

  • Code generation and completion
  • Programming task understanding
  • Benchmark-verified performance on coding tasks
  • Support for various programming challenges

Frequently Asked Questions

Q: What makes this model unique?

The model stands out for its efficient size-to-performance ratio, achieving competitive results on coding benchmarks while maintaining a relatively small 1B parameter count. It's particularly notable for its practical implementation and easy-to-use inference pipeline.

Q: What are the recommended use cases?

This model is ideal for code generation tasks, particularly in scenarios requiring Python code generation. It's well-suited for automated coding assistance, code completion, and programming education tools, with demonstrated capability in solving algorithmic problems.

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