Text Generation
Safetensors
GGUF
Russian
English
mistral3
reasoning
r1
deepseek-r1
ministral
cot
chain-of-thought
russian
code
math
unsloth
llama.cpp
lmstudio
ollama
vllm
jan
openclaw
hermes-agent
conversational
Eval Results (legacy)
Instructions to use fwizzer1/Fwizzer-R1-3B-RU-v2 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-v2 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-v2 # Run inference directly in the terminal: llama cli -hf fwizzer1/Fwizzer-R1-3B-RU-v2
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-v2 # Run inference directly in the terminal: llama cli -hf fwizzer1/Fwizzer-R1-3B-RU-v2
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf fwizzer1/Fwizzer-R1-3B-RU-v2 # Run inference directly in the terminal: ./build/bin/llama cli -hf fwizzer1/Fwizzer-R1-3B-RU-v2
Use Docker
docker model run hf.co/fwizzer1/Fwizzer-R1-3B-RU-v2
- Llama new
- LM Studio
- Jan
- vLLM
How to use fwizzer1/Fwizzer-R1-3B-RU-v2 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-v2" # 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-v2", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/fwizzer1/Fwizzer-R1-3B-RU-v2
- Ollama
How to use fwizzer1/Fwizzer-R1-3B-RU-v2 with Ollama:
ollama run hf.co/fwizzer1/Fwizzer-R1-3B-RU-v2
- Unsloth Desktop
- Pi
How to use fwizzer1/Fwizzer-R1-3B-RU-v2 with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf fwizzer1/Fwizzer-R1-3B-RU-v2
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "fwizzer1/Fwizzer-R1-3B-RU-v2" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use fwizzer1/Fwizzer-R1-3B-RU-v2 with Docker Model Runner:
docker model run hf.co/fwizzer1/Fwizzer-R1-3B-RU-v2
- Lemonade
How to use fwizzer1/Fwizzer-R1-3B-RU-v2 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull fwizzer1/Fwizzer-R1-3B-RU-v2
Run and chat with the model
lemonade run user.Fwizzer-R1-3B-RU-v2-{{QUANT_TAG}}List all available models
lemonade list
- Hermes Agent
How to use fwizzer1/Fwizzer-R1-3B-RU-v2 with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf fwizzer1/Fwizzer-R1-3B-RU-v2
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default fwizzer1/Fwizzer-R1-3B-RU-v2
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use fwizzer1/Fwizzer-R1-3B-RU-v2 with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf fwizzer1/Fwizzer-R1-3B-RU-v2
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "fwizzer1/Fwizzer-R1-3B-RU-v2" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
Update active EN LoRA adapter (step 2100/2500)
Browse files- en/adapter_model.safetensors +1 -1
- en/chat_template.jinja +2 -44
- en/tokenizer_config.json +2 -3
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{{ bos_token }}{%- set default_system = 'You are a thinking neural network and your name is Fwizzer-R1-3B-RU. Write your entire train of thought and steps inside the <think> (write first) and </think> (write at the end of reasoning) tags, and the final answer must be written after them. Always respond and reason strictly in the language the user addressed you in (for example, if the question is in Russian - answer in Russian, if in English - in English, if in Chinese - in Chinese).' -%}{%- if messages[0]['role'] == 'system' -%} {%- set system_message = messages[0]['content'] -%} {%- set loop_messages = messages[1:] -%}{%- else -%} {%- set system_message = default_system -%} {%- set loop_messages = messages -%}{%- endif -%}{%- for message in loop_messages -%} {%- if message['role'] == 'user' -%} {%- if loop.first and system_message -%} {{ '[SYSTEM_PROMPT]' + system_message + '[/SYSTEM_PROMPT][INST]' + message['content'] + '[/INST]' }} {%- else -%} {{ '[INST]' + message['content'] + '[/INST]' }} {%- endif -%} {%- elif message['role'] == 'assistant' -%} {{ message['content'] + eos_token }} {%- endif -%}{%- endfor -%}{%- if add_generation_prompt -%} {{ '<think>
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