Text Generation
English
deepseek_v4
deepseek
Mixture of Experts
sovereign
agentic
speculative-decoding
4-bit precision
gptq
Instructions to use Codexcoder/deepseek-v4-sovereign with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Local Apps Settings
- vLLM
How to use Codexcoder/deepseek-v4-sovereign with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Codexcoder/deepseek-v4-sovereign" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Codexcoder/deepseek-v4-sovereign", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Codexcoder/deepseek-v4-sovereign
- SGLang
How to use Codexcoder/deepseek-v4-sovereign with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "Codexcoder/deepseek-v4-sovereign" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Codexcoder/deepseek-v4-sovereign", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "Codexcoder/deepseek-v4-sovereign" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Codexcoder/deepseek-v4-sovereign", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Codexcoder/deepseek-v4-sovereign with Docker Model Runner:
docker model run hf.co/Codexcoder/deepseek-v4-sovereign
| license: mit | |
| language: | |
| - en | |
| tags: | |
| - deepseek | |
| - moe | |
| - sovereign | |
| - text-generation | |
| - agentic | |
| - speculative-decoding | |
| pipeline_tag: text-generation | |
| base_model: deepseek-ai/DeepSeek-V4-Flash-0731 | |
| inference: false | |
| # 🌌 deepseek-v4-sovereign — the new sovereign AI model | |
| **SOVEREIGN's flagship model.** A sovereign-tuned derivative of | |
| [`deepseek-ai/DeepSeek-V4-Flash-0731`](https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash-0731) | |
| (304B MoE, MIT license) with an extended reasoning budget, 1M-token context, | |
| and DSpark speculative decoding — tuned on private, user-owned corpora only. | |
| ## Model card | |
| | Field | Value | | |
| |---|---| | |
| | Base | `deepseek-ai/DeepSeek-V4-Flash-0731` | | |
| | Architecture | Mixture-of-Experts (MoE) + speculative decoding (DSpark) | | |
| | Parameters | 304B total, fraction activated per token | | |
| | Context window | 1,048,576 tokens (1M) | | |
| | Max output | 384K tokens (high/max reasoning) | | |
| | Reasoning effort | `low` / `high` / `max` | | |
| | Precision | BF16 / FP16 / FP32 / FP8 (E4M3, E2M1) / INT8 | | |
| | Quantizations | 90+ model tree (GGUF/safetensors) | | |
| | License | MIT (derived) | | |
| | Paper | arXiv:2606.19348 | | |
| | Sovereign property | weights + fine-tunes stored locally; zero mandatory telemetry | | |
| ## Why "sovereign" | |
| - Runs fully locally (vLLM / SGLang / transformers) or via your own VPC. | |
| - No mandatory external API calls; HF router (`router.huggingface.co/v1`) | |
| is an *option*, not a dependency. | |
| - Fine-tuning data, adapters, and inference logs stay under your control. | |
| ## Deployment | |
| ```bash | |
| # vLLM (4×GB300 node) — DSpark speculative decoding enabled with one flag | |
| vllm serve deepseek-ai/DeepSeek-V4-Flash-0731 \ | |
| --trust-remote-code --kv-cache-dtype fp8 --block-size 256 \ | |
| --data-parallel-size 4 --enable-expert-parallel \ | |
| --moe-backend deep_gemm_mega_moe \ | |
| --speculative-config '{"method":"dspark","num_speculative_tokens":7,"draft_sample_method":"greedy"}' | |
| # SGLang | |
| sglang serve --trust-remote-code \ | |
| --model-path deepseek-ai/DeepSeek-V4-Flash-0731 \ | |
| --tp 4 --moe-runner-backend flashinfer_mxfp4 \ | |
| --speculative-algorithm DSPARK --chunked-prefill-size 4096 | |
| ``` | |
| Recommended sampling for agentic scenarios: `temperature=1.0, top_p=0.95`; | |
| otherwise `top_p=1.0`. | |
| ## Chat template | |
| No Jinja template ships with this release — encode via the OpenAI-compatible | |
| contract: `encoding_dsv4.encode_messages(messages, thinking_mode="thinking", | |
| reasoning_effort="max")` (see `models/deepseek-v4-flash-0731/` docs and | |
| `api_examples/`). | |