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fwizzer1
/
Fwizzer-R1-3B-RU

Text Generation
Safetensors
GGUF
Russian
English
mistral3
reasoning
deepseek-r1
ru-deepthink-11k
mistral
conversational
Model card Files Files and versions
xet
Community

Instructions to use fwizzer1/Fwizzer-R1-3B-RU 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 fwizzer1/Fwizzer-R1-3B-RU 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 fwizzer1/Fwizzer-R1-3B-RU
    # Run inference directly in the terminal:
    llama cli -hf fwizzer1/Fwizzer-R1-3B-RU
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama serve -hf fwizzer1/Fwizzer-R1-3B-RU
    # Run inference directly in the terminal:
    llama cli -hf fwizzer1/Fwizzer-R1-3B-RU
    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 fwizzer1/Fwizzer-R1-3B-RU
    # Run inference directly in the terminal:
    ./llama-cli -hf fwizzer1/Fwizzer-R1-3B-RU
    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 fwizzer1/Fwizzer-R1-3B-RU
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf fwizzer1/Fwizzer-R1-3B-RU
    Use Docker
    docker model run hf.co/fwizzer1/Fwizzer-R1-3B-RU
  • LM Studio
  • Jan
  • vLLM

    How to use fwizzer1/Fwizzer-R1-3B-RU with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "fwizzer1/Fwizzer-R1-3B-RU"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "fwizzer1/Fwizzer-R1-3B-RU",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/fwizzer1/Fwizzer-R1-3B-RU
  • Ollama

    How to use fwizzer1/Fwizzer-R1-3B-RU with Ollama:

    ollama run hf.co/fwizzer1/Fwizzer-R1-3B-RU
  • Unsloth Desktop
  • Docker Model Runner

    How to use fwizzer1/Fwizzer-R1-3B-RU with Docker Model Runner:

    docker model run hf.co/fwizzer1/Fwizzer-R1-3B-RU
  • Lemonade

    How to use fwizzer1/Fwizzer-R1-3B-RU with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull fwizzer1/Fwizzer-R1-3B-RU
    Run and chat with the model
    lemonade run user.Fwizzer-R1-3B-RU-{{QUANT_TAG}}
    List all available models
    lemonade list
  • Atomic Chat
Fwizzer-R1-3B-RU
5.91 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 51 commits
fwizzer1's picture
fwizzer1
Update chat_template.jinja with mandatory <think> prefill
2472e0c verified 3 days ago
  • .gitattributes
    2.17 kB
    Rename GGUF files to include -RU- prefix 3 days ago
  • Fwizzer-R1-3B-RU-Max.gguf
    3.65 GB
    xet
    Rename GGUF files to include -RU- prefix 3 days ago
  • Fwizzer-R1-3B-RU-Speed.gguf
    2.15 GB
    xet
    Rename GGUF files to include -RU- prefix 3 days ago
  • Fwizzer-R1.preset.json
    1.94 kB
    Fix Fwizzer-R1.preset.json encoding, system prompt, and reasoning parser 3 days ago
  • README.md
    2.21 kB
    Update README with Speed and Max filenames 9 days ago
  • adapter_config.json
    1.5 kB
    Upload model trained with Unsloth 12 days ago
  • adapter_model.safetensors
    98.9 MB
    xet
    Upload model trained with Unsloth 12 days ago
  • chat_template.jinja
    1.28 kB
    Update chat_template.jinja with mandatory <think> prefill 3 days ago
  • config.json
    2.09 kB
    Enable 1M Context (1,048,576 tokens) with YaRN RoPE scaling 10 days ago
  • model.yaml
    442 Bytes
    Update model.yaml with Speed and Max filenames 9 days ago
  • tokenizer.json
    17.1 MB
    xet
    Upload model trained with Unsloth 12 days ago
  • tokenizer_config.json
    200 kB
    Add native deepseek reasoning token format to tokenizer_config.json 10 days ago