Original model description:

license: other license_name: deepseek license_link: LICENSE datasets: - wyt2000/InverseCoder-DS-6.7B-Evol-Instruct-90K - ise-uiuc/Magicoder-Evol-Instruct-110K library_name: transformers pipeline_tag: text-generation tags: - code model-index: - name: InverseCoder-DS-6.7B results: - task: type: text-generation dataset: type: openai_humaneval name: HumanEval metrics: - name: pass@1 type: pass@1 value: 0.799 verified: false - task: type: text-generation dataset: type: openai_humaneval name: HumanEval(+) metrics: - name: pass@1 type: pass@1 value: 0.768 verified: false - task: type: text-generation dataset: type: mbpp name: MBPP metrics: - name: pass@1 type: pass@1 value: 0.786 verified: false - task: type: text-generation dataset: type: mbpp name: MBPP(+) metrics: - name: pass@1 type: pass@1 value: 0.690 verified: false - task: type: text-generation dataset: type: ds1000 name: DS-1000 (Overall Completion) metrics: - name: pass@1 type: pass@1 value: 0.442 verified: false - task: type: text-generation dataset: type: nuprl/MultiPL-E name: MultiPL-HumanEval (Java) metrics: - name: pass@1 type: pass@1 value: 0.607 verified: false - task: type: text-generation dataset: type: nuprl/MultiPL-E name: MultiPL-HumanEval (JavaScript) metrics: - name: pass@1 type: pass@1 value: 0.701 verified: false - task: type: text-generation dataset: type: nuprl/MultiPL-E name: MultiPL-HumanEval (C++) metrics: - name: pass@1 type: pass@1 value: 0.705 verified: false - task: type: text-generation dataset: type: nuprl/MultiPL-E name: MultiPL-HumanEval (PHP) metrics: - name: pass@1 type: pass@1 value: 0.636 verified: false - task: type: text-generation dataset: type: nuprl/MultiPL-E name: MultiPL-HumanEval (Swift) metrics: - name: pass@1 type: pass@1 value: 0.530 verified: false - task: type: text-generation dataset: type: nuprl/MultiPL-E name: MultiPL-HumanEval (Rust) metrics: - name: pass@1 type: pass@1 value: 0.574 verified: false - task: type: text-generation dataset: type: nuprl/MultiPL-E name: MultiPL-HumanEval (Average for non-python languages) metrics: - name: pass@1 type: pass@1 value: 0.626 verified: false

InverseCoder: Unleashing the Power of Instruction-Tuned Code LLMs with Inverse-Instruct

InverseCoder is a series of code LLMs instruction-tuned by generating data from itself through Inverse-Instruct.

Models and Datasets

	Base Model	InverseCoder	Dataset
6.7B	deepseek-ai/deepseek-coder-6.7b-base	wyt2000/InverseCoder-DS-6.7B <= You are here	wyt2000/InverseCoder-DS-6.7B-Evol-Instruct-90K
7B	codellama/CodeLlama-7b-Python-hf	wyt2000/InverseCoder-CL-7B	wyt2000/InverseCoder-CL-7B-Evol-Instruct-90K
13B	codellama/CodeLlama-13b-Python-hf	wyt2000/InverseCoder-CL-13B	wyt2000/InverseCoder-CL-13B-Evol-Instruct-90K

Usage

Similar to Magicoder-S-DS-6.7B, use the code below to get started with the model. Make sure you installed the transformers library.

from transformers import pipeline
import torch
INVERSECODER_PROMPT = """You are an exceptionally intelligent coding assistant that consistently delivers accurate and reliable responses to user instructions.
@@ Instruction
{instruction}
@@ Response
"""
instruction = <Your code instruction here>
prompt = INVERSECODER_PROMPT.format(instruction=instruction)
generator = pipeline(
    model="wyt2000/InverseCoder-DS-6.7B",
    task="text-generation",
    torch_dtype=torch.bfloat16,
    device_map="auto",
)
result = generator(prompt, max_length=1024, num_return_sequences=1, temperature=0.0)
print(result[0]["generated_text"])

Paper

Arxiv: https://arxiv.org/abs/2407.05700

Please cite the paper if you use the models or datasets from InverseCoder.

@misc{wu2024inversecoderunleashingpowerinstructiontuned,
      title={InverseCoder: Unleashing the Power of Instruction-Tuned Code LLMs with Inverse-Instruct}, 
      author={Yutong Wu and Di Huang and Wenxuan Shi and Wei Wang and Lingzhe Gao and Shihao Liu and Ziyuan Nan and Kaizhao Yuan and Rui Zhang and Xishan Zhang and Zidong Du and Qi Guo and Yewen Pu and Dawei Yin and Xing Hu and Yunji Chen},
      year={2024},
      eprint={2407.05700},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2407.05700}, 
}

Code

Official code repo for Inverse-Instruct (under development).

Acknowledgements

Magicoder: Training code, original datasets and data decontamination
DeepSeek-Coder: Base model for InverseCoder-DS
CodeLlama: Base model for InverseCoder-CL
AutoMathText: Self-evaluation and data selection method