uukuguy/speechless-coding-7b-16k-tora
The uukuguy/speechless-coding-7b-16k-tora is a 7 billion parameter language model fine-tuned by uukuguy, based on llm_agents/tora-code-7b-v1.0, with an extended context window of 16,384 tokens. This model is specifically optimized for improving reasoning, planning, and code generation abilities. It demonstrates strong performance in programming tasks, achieving 52.44 on HumanEval-Python and competitive scores across multiple programming languages in MultiPL-E benchmarks.
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Model Overview
The uukuguy/speechless-coding-7b-16k-tora is a 7 billion parameter model, fine-tuned from llm_agents/tora-code-7b-v1.0, designed to enhance reasoning, planning, and coding capabilities. It features an extended context window of 16,384 tokens and accepts the Alpaca instruction format for prompting.
Key Capabilities & Performance
This model excels in code generation and problem-solving, as evidenced by its benchmark results:
- HumanEval-Python: Achieves a score of 52.44, performing comparably to larger CodeLlama-34B variants.
- MultiPL-E: Demonstrates proficiency across various programming languages, including Python (55.96), JavaScript (46.93), and C++ (37.48).
Training Details
The model was fine-tuned on a diverse dataset of 177,333 samples, totaling 316 MB, specifically curated for coding, reasoning, and planning tasks. The training data includes filtered categories from:
jondurbin/airoboros-2.2(coding, reasoning, planning)Open-Orca/OpenOrca(COT category from GPT-4 data)garage-bAInd/Open-PlatypusWizardLM/WizardLM_evol_instruct_V2_196k(coding conversation)TokenBender/python_eval_instruct_51k(Python-specific outputs)
Use Cases
This model is particularly well-suited for applications requiring:
- Code generation and completion
- Programming problem-solving
- Reasoning and planning in technical contexts
- Instruction-following for coding tasks