> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.nvidia.com/nemo/automodel/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nemo/automodel/_mcp/server.

# deepseek-llm-7b-chat

> Reference deepseek-llm-7b-chat checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources.

[DeepSeek](https://github.com/deepseek-ai) is a series of open-weight language models from DeepSeek AI. The first-generation models (V1/V2) use standard transformer decoder and Multi-head Latent Attention architectures.

Use this page as a checkpoint and architecture reference. Set up NeMo AutoModel with the
[latest container](https://catalog.ngc.nvidia.com/orgs/nvidia/containers/nemo-automodel) or follow the
[installation instructions](/get-started/installation).

## Model Reference

### Model Architecture

| Property                  | Value                                             |
| ------------------------- | ------------------------------------------------- |
| Task                      | Text Generation                                   |
| Architecture              | `DeepseekForCausalLM`                             |
| Parameters                | 7B                                                |
| Hugging Face Organization | [deepseek-ai](https://huggingface.co/deepseek-ai) |

* `DeepseekForCausalLM` - DeepSeek v1/v2 dense models

### Available Models

| Model                | HF ID                                                                                         |
| -------------------- | --------------------------------------------------------------------------------------------- |
| DeepSeek LLM 7B Chat | [`deepseek-ai/deepseek-llm-7b-chat`](https://huggingface.co/deepseek-ai/deepseek-llm-7b-chat) |

## Related Resources

* [LLM Fine-Tuning Guide](/recipes-e2e-examples/sft-peft)