Each model is pre-trained on project-level code corpus by employing a window size of 16K and an extra fill-in-the-blank task, to support project-level code completion and infilling. For coding capabilities, DeepSeek Coder achieves state-of-the-art performance among open-source code models on...
DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence - JiangCa/DeepSeek-Coder-V2
DeepSeek-Coder的训练数据集由以下几部分组成：源代码（Source Code）：占数据集的87%，这些代码来源于...
源代码(Source Code):占数据集的87%,这些代码来源于GitHub上的公共仓库,并且只保留了87种编程语言的代码。为了减少需要处理的数据量,应用了类似于StarCoder项目中使用的过滤规则,以初步筛选出较低质量的代码。 英文代码相关自然语言语料库(English code-related natural language corpus):占数据集的10%,这些材料来自Gi...
DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence 1 1 5 DeepSeek-V3 DeepSeek-V3 4 8 11 DeepSeek-R1 DeepSeek-R1 1 16 9 自定义精选项目 最多可选取 6 个公开仓库 还能勾选6个 语言: 全部 全部 JavaScript ...
Model Weights & Demo Code Preparation First, clone our DeepSeek-V3 GitHub repository: git clone https://github.com/deepseek-ai/DeepSeek-V3.git Navigate to the inference folder and install dependencies listed in requirements.txt. Easiest way is to use a package manager like conda or uv to...
In a future post I'll walk you through the extension code and explain how to call models hosted locally using Ollama. Feel free to subscribe to get notified. Features and Benefits Open-Source and Extendable As anopen-source project, the DeepSeek for GitHu...
Due to the constraints of HuggingFace, the open-source code currently experiences slower performance than our internal codebase when running on GPUs with Huggingface. To facilitate the efficient execution of our model, we offer a dedicated vllm solution that optimizes performance for running our mode...
2、CodeLlama-70B-Instruct 1月29日Meta新开源的代码大模型CodeLlama-70B-Instruct,可以说从去年8月到现在,半年磨一剑。在EvalPlus排行榜(https://evalplus.github.io/leaderboard.html)上,最新的CodeLlama-70B-Instruct的HumanEval paas@1评分58.5分,低于GPT-3.5,相比CodeLlama-34B-Instruct进步不少。
git clone https://github.com/going-doer/Paper2Code cd Paper2Code git clone https://github.com/allenai/s2orc-doc2json.git cd scripts bash run.sh 输出结果如下 outputs ├── Transformer │ ├── analyzing_artifacts │ ├── coding_artifacts ...