Text Generation
Safetensors
GGUF
English
mixture-of-experts
Mixture of Experts
deepseek
multi-head-latent-attention
mla
multi-token-prediction
from-scratch
tiny
Instructions to use edededdy/ShallowSeek-mini-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use edededdy/ShallowSeek-mini-base with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf edededdy/ShallowSeek-mini-base:F16 # Run inference directly in the terminal: llama cli -hf edededdy/ShallowSeek-mini-base:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf edededdy/ShallowSeek-mini-base:F16 # Run inference directly in the terminal: llama cli -hf edededdy/ShallowSeek-mini-base:F16
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf edededdy/ShallowSeek-mini-base:F16 # Run inference directly in the terminal: ./llama-cli -hf edededdy/ShallowSeek-mini-base:F16
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf edededdy/ShallowSeek-mini-base:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf edededdy/ShallowSeek-mini-base:F16
Use Docker
docker model run hf.co/edededdy/ShallowSeek-mini-base:F16
- LM Studio
- Jan
- vLLM
How to use edededdy/ShallowSeek-mini-base with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "edededdy/ShallowSeek-mini-base" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "edededdy/ShallowSeek-mini-base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/edededdy/ShallowSeek-mini-base:F16
- Ollama
How to use edededdy/ShallowSeek-mini-base with Ollama:
ollama run hf.co/edededdy/ShallowSeek-mini-base:F16
- Unsloth Desktop
- Docker Model Runner
How to use edededdy/ShallowSeek-mini-base with Docker Model Runner:
docker model run hf.co/edededdy/ShallowSeek-mini-base:F16
- Lemonade
How to use edededdy/ShallowSeek-mini-base with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull edededdy/ShallowSeek-mini-base:F16
Run and chat with the model
lemonade run user.ShallowSeek-mini-base-F16
List all available models
lemonade list
- Atomic Chat
Download tokenizer.json from edededdy/ShallowSeek-mini-base: direct link, hf CLI and curl.
- Browser
- Download file 230 kB
-
https://huggingface.co/edededdy/ShallowSeek-mini-base/resolve/main/tokenizer.json
- Command line
-
hf download hf://edededdy/ShallowSeek-mini-base/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/edededdy/ShallowSeek-mini-base/resolve/main/tokenizer.json
230 kB
| 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