Quantization made by Richard Erkhov. [Github](https://github.com/RichardErkhov) [Discord](https://discord.gg/pvy7H8DZMG) [Request more models](https://github.com/RichardErkhov/quant_request) ReflectionCoder-CL-34B - GGUF - Model creator: https://huggingface.co/SenseLLM/ - Original model: https://huggingface.co/SenseLLM/ReflectionCoder-CL-34B/ | Name | Quant method | Size | | ---- | ---- | ---- | | [ReflectionCoder-CL-34B.Q2_K.gguf](https://huggingface.co/RichardErkhov/SenseLLM_-_ReflectionCoder-CL-34B-gguf/blob/main/ReflectionCoder-CL-34B.Q2_K.gguf) | Q2_K | 11.65GB | | [ReflectionCoder-CL-34B.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/SenseLLM_-_ReflectionCoder-CL-34B-gguf/blob/main/ReflectionCoder-CL-34B.Q3_K_S.gguf) | Q3_K_S | 13.6GB | | [ReflectionCoder-CL-34B.Q3_K.gguf](https://huggingface.co/RichardErkhov/SenseLLM_-_ReflectionCoder-CL-34B-gguf/blob/main/ReflectionCoder-CL-34B.Q3_K.gguf) | Q3_K | 15.19GB | | [ReflectionCoder-CL-34B.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/SenseLLM_-_ReflectionCoder-CL-34B-gguf/blob/main/ReflectionCoder-CL-34B.Q3_K_M.gguf) | Q3_K_M | 15.19GB | | [ReflectionCoder-CL-34B.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/SenseLLM_-_ReflectionCoder-CL-34B-gguf/blob/main/ReflectionCoder-CL-34B.Q3_K_L.gguf) | Q3_K_L | 16.55GB | | [ReflectionCoder-CL-34B.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/SenseLLM_-_ReflectionCoder-CL-34B-gguf/blob/main/ReflectionCoder-CL-34B.IQ4_XS.gguf) | IQ4_XS | 16.99GB | | [ReflectionCoder-CL-34B.Q4_0.gguf](https://huggingface.co/RichardErkhov/SenseLLM_-_ReflectionCoder-CL-34B-gguf/blob/main/ReflectionCoder-CL-34B.Q4_0.gguf) | Q4_0 | 17.74GB | | [ReflectionCoder-CL-34B.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/SenseLLM_-_ReflectionCoder-CL-34B-gguf/blob/main/ReflectionCoder-CL-34B.IQ4_NL.gguf) | IQ4_NL | 17.92GB | | [ReflectionCoder-CL-34B.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/SenseLLM_-_ReflectionCoder-CL-34B-gguf/blob/main/ReflectionCoder-CL-34B.Q4_K_S.gguf) | Q4_K_S | 17.87GB | | [ReflectionCoder-CL-34B.Q4_K.gguf](https://huggingface.co/RichardErkhov/SenseLLM_-_ReflectionCoder-CL-34B-gguf/blob/main/ReflectionCoder-CL-34B.Q4_K.gguf) | Q4_K | 18.83GB | | [ReflectionCoder-CL-34B.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/SenseLLM_-_ReflectionCoder-CL-34B-gguf/blob/main/ReflectionCoder-CL-34B.Q4_K_M.gguf) | Q4_K_M | 18.83GB | | [ReflectionCoder-CL-34B.Q4_1.gguf](https://huggingface.co/RichardErkhov/SenseLLM_-_ReflectionCoder-CL-34B-gguf/blob/main/ReflectionCoder-CL-34B.Q4_1.gguf) | Q4_1 | 19.69GB | | [ReflectionCoder-CL-34B.Q5_0.gguf](https://huggingface.co/RichardErkhov/SenseLLM_-_ReflectionCoder-CL-34B-gguf/blob/main/ReflectionCoder-CL-34B.Q5_0.gguf) | Q5_0 | 21.64GB | | [ReflectionCoder-CL-34B.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/SenseLLM_-_ReflectionCoder-CL-34B-gguf/blob/main/ReflectionCoder-CL-34B.Q5_K_S.gguf) | Q5_K_S | 21.64GB | | [ReflectionCoder-CL-34B.Q5_K.gguf](https://huggingface.co/RichardErkhov/SenseLLM_-_ReflectionCoder-CL-34B-gguf/blob/main/ReflectionCoder-CL-34B.Q5_K.gguf) | Q5_K | 22.2GB | | [ReflectionCoder-CL-34B.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/SenseLLM_-_ReflectionCoder-CL-34B-gguf/blob/main/ReflectionCoder-CL-34B.Q5_K_M.gguf) | Q5_K_M | 22.2GB | | [ReflectionCoder-CL-34B.Q5_1.gguf](https://huggingface.co/RichardErkhov/SenseLLM_-_ReflectionCoder-CL-34B-gguf/blob/main/ReflectionCoder-CL-34B.Q5_1.gguf) | Q5_1 | 23.59GB | | [ReflectionCoder-CL-34B.Q6_K.gguf](https://huggingface.co/RichardErkhov/SenseLLM_-_ReflectionCoder-CL-34B-gguf/blob/main/ReflectionCoder-CL-34B.Q6_K.gguf) | Q6_K | 25.78GB | | [ReflectionCoder-CL-34B.Q8_0.gguf](https://huggingface.co/RichardErkhov/SenseLLM_-_ReflectionCoder-CL-34B-gguf/blob/main/ReflectionCoder-CL-34B.Q8_0.gguf) | Q8_0 | 33.39GB | Original model description: --- license: apache-2.0 datasets: - SenseLLM/ReflectionSeq-GPT - SenseLLM/ReflectionSeq-DS language: - en --- ## ReflectionCoder: Learning from Reflection Sequence for Enhanced One-off Code Generation

📄 Paper🏠 Repo🤖 Models📚 Datasets

## 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! ![](method.png)
## 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": ""} ] 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)