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---
language:
- en
license: apache-2.0
datasets:
- SenseLLM/ReflectionSeq-GPT
- SenseLLM/ReflectionSeq-DS
model-index:
- name: ReflectionCoder-CL-34B
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: IFEval (0-Shot)
type: HuggingFaceH4/ifeval
args:
num_few_shot: 0
metrics:
- type: inst_level_strict_acc and prompt_level_strict_acc
value: 40.08
name: strict accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=SenseLLM/ReflectionCoder-CL-34B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: BBH (3-Shot)
type: BBH
args:
num_few_shot: 3
metrics:
- type: acc_norm
value: 14.26
name: normalized accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=SenseLLM/ReflectionCoder-CL-34B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MATH Lvl 5 (4-Shot)
type: hendrycks/competition_math
args:
num_few_shot: 4
metrics:
- type: exact_match
value: 1.96
name: exact match
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=SenseLLM/ReflectionCoder-CL-34B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GPQA (0-shot)
type: Idavidrein/gpqa
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 0.11
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=SenseLLM/ReflectionCoder-CL-34B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MuSR (0-shot)
type: TAUR-Lab/MuSR
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 10.4
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=SenseLLM/ReflectionCoder-CL-34B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU-PRO (5-shot)
type: TIGER-Lab/MMLU-Pro
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 4.71
name: accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=SenseLLM/ReflectionCoder-CL-34B
name: Open LLM Leaderboard
---
## ReflectionCoder: Learning from Reflection Sequence for Enhanced One-off Code Generation
<p align="center">
<a href="https://arxiv.org/abs/2405.17057">📄 Paper</a> •
<a href="https://github.com/SenseLLM/ReflectionCoder">🏠 Repo</a> •
<a href="https://huggingface.co/SenseLLM/ReflectionCoder-DS-33B">🤖 Models</a> •
<a href="https://huggingface.co/datasets/SenseLLM/ReflectionSeq-GPT">📚 Datasets </a>
</p>
## Introduction
ReflectionCoder is a novel approach that effectively leverages reflection sequences constructed by integrating compiler feedback to improve one-off code generation performance. Please refer to our paper and repo for more details!
<hr>
## Models
| Model | Checkpoint | Size | HumanEval (+) | MBPP (+) | License|
|:-------|:------------|:------|:---------------|:----------|:--------|
| ReflectionCoder-CL-7B | 🤗 [HF Link](https://huggingface.co/SenseLLM/ReflectionCoder-CL-7B) | 7B | 75.0 (68.9) | 72.2 (61.4) | [Llama2](https://ai.meta.com/llama/license/) |
| ReflectionCoder-CL-34B | 🤗 [HF Link](https://huggingface.co/SenseLLM/ReflectionCoder-CL-34B) | 34B | 70.7 (66.5) | 68.4 (56.6) | [Llama2](https://ai.meta.com/llama/license/) |
| ReflectionCoder-DS-6.7B | 🤗 [HF Link](https://huggingface.co/SenseLLM/ReflectionCoder-DS-6.7B) | 6.7B | 80.5 (74.4) | 81.5 (69.6) | [DeepSeek](https://github.com/deepseek-ai/DeepSeek-Coder/blob/main/LICENSE-MODEL) |
| ReflectionCoder-DS-33B | 🤗 [HF Link](https://huggingface.co/SenseLLM/ReflectionCoder-DS-33B) | 33B | 82.9 (76.8) | 84.1 (72.0) | [DeepSeek](https://github.com/deepseek-ai/DeepSeek-Coder/blob/main/LICENSE-MODEL) |
## Datasets
| Dataset | Link | License |
|:-------------------|:----------------|:----------------------------------------------|
| ReflectionSeq-GPT | 🤗 [HF Link](https://huggingface.co/datasets/SenseLLM/ReflectionSeq-GPT) | [License](LICENSE) |
| ReflectionSeq-DS | 🤗 [HF Link](https://huggingface.co/datasets/SenseLLM/ReflectionSeq-DS) | [License](LICENSE) |
## How to Use
#### Chat Format
Following chat templates of most models, we use two special tokens to wrap the message of user and assistant, *i.e.*, ``<|user|>``, ``<|assistant|>``, and ``<|endofmessage|>``. Furthermore, we use two special tokens to wrap the content of different blocks, *i.e.*, ``<|text|>`` and ``<|endofblock|>``. You can use the following template to prompt our ReflectionCoder.
```python
import torch
from transformers import pipeline
chat = [
{"role": "user", "content": "<Your code instruction here>"}
]
generator = pipeline(
model="SenseLLM/ReflectionCoder-CL-34B",
task="text-generation",
torch_dtype=torch.bfloat16,
device_map="auto",
)
result = generator(chat, max_length=128, num_return_sequences=1)
print(result)
```
Please refer to our [GitHub Repo](https://github.com/SenseLLM/ReflectionCoder) for more technical details.
## Citation
If you find this repo useful for your research, please kindly cite our paper:
```
@misc{ren2024reflectioncoder,
title={ReflectionCoder: Learning from Reflection Sequence for Enhanced One-off Code Generation},
author={Houxing Ren and Mingjie Zhan and Zhongyuan Wu and Aojun Zhou and Junting Pan and Hongsheng Li},
year={2024},
eprint={2405.17057},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
```
## Acknowledgments
We thank the following amazing projects that truly inspired us:
- [CodeLlama](https://ai.meta.com/research/publications/code-llama-open-foundation-models-for-code/)
- [DeepSeek-Coder](https://github.com/deepseek-ai/DeepSeek-Coder)
- [WizardCoder](https://github.com/nlpxucan/WizardLM/tree/main/WizardCoder)
- [Evol-CodeAlpaca-v1](https://huggingface.co/datasets/theblackcat102/evol-codealpaca-v1)
- [MagiCoder](https://github.com/ise-uiuc/magicoder/tree/main)
- [EvalPlus](https://github.com/evalplus/evalplus)
- [OpenCoderInterpreter](https://github.com/OpenCodeInterpreter/OpenCodeInterpreter/tree/main)
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_SenseLLM__ReflectionCoder-CL-34B)
| Metric |Value|
|-------------------|----:|
|Avg. |11.92|
|IFEval (0-Shot) |40.08|
|BBH (3-Shot) |14.26|
|MATH Lvl 5 (4-Shot)| 1.96|
|GPQA (0-shot) | 0.11|
|MuSR (0-shot) |10.40|
|MMLU-PRO (5-shot) | 4.71|
|