DeepSeek-Coder-Lite

About

What DeepSeek-Coder-Lite is

DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence 1. Introduction We present DeepSeek-Coder-V2, an open-source Mixture-of-Experts (MoE) code language model that achieves performance comparable to GPT4-Turbo in code-specific tasks. Specifically, DeepSeek-Coder-V2 is further pre-trained from an intermediate checkpoint of DeepSeek-V2 with additional 6 trillion tokens. Through this continued pre-training, DeepSeek-Coder-V2 substantially enhances the coding and mathematical reasoning capabilities of DeepSeek-V2, while maintaining comparable performance in general language tasks. Compared to DeepSeek-Coder-33B, DeepSeek-Coder-V2 demonstrates significant advancements in various aspects of code-related tasks, as well as reasoning and general capabilities. Additionally, DeepSeek-Coder-V2 expands its support for programming languages from 86 to 338, while extending the context length from 16K to 128K. In standard benchmark evaluations, DeepSeek-Coder-V2 achieves superior performance compared to closed-source models such as GPT4-Turbo, Claude 3 Opus, and Gemini 1.5 Pro in coding and math benchmarks. The list of supported programming languages can be found here. 2. Model Downloads We release the DeepSeek-Coder-V2 with 16B and 236B parameters based on the DeepSeekMoE framework, which has actived parameters of only 2.4B and 21B , including base and instruct models, to the public. 3. Chat Website You can chat with the DeepSeek-Coder-V2 on DeepSeek's official website: coder.deepseek.com 4. API Platform We also provide OpenAI-Compatible API at DeepSeek Platform: platform.deepseek.com, and you can also pay-as-you-go at an unbeatable price. 5. How to run locally Here, we provide some examples of how to use DeepSeek-Coder-V2-Lite model. If you want to utilize DeepSeek-Coder-V2 in BF16 format for inference, 80GB8 GPUs are required. Inference with Huggingface's Transformers You can directly employ Huggingface's Transformers for model inference. Code Completion Code Insertion Chat Completion The complete chat template can be found within tokenizerconfig.json located in the huggingface model repository. An example of chat template is as belows: You ca

Summarised from the published model card. Read the full card on the HuggingFace links below.

Specifications

What it is

How it works

How language models work

Variants

Sizes & precisions

Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys deepseek-coder-lite for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (deepseek-coder-lite below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/chat/completions \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"deepseek-coder-lite","messages":[{"role":"user","content":"Hello"}]}'

Details

Languages, data & research

Papers

Licence

Commercial licence needed

Sources

Weights & code

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