Text Generation
Safetensors
GGUF
English
Russian
mistral3
reasoning
r1
deepseek-r1
ministral
cot
chain-of-thought
english
code
math
unsloth
llama.cpp
lmstudio
ollama
vllm
jan
openclaw
hermes-agent
conversational
Eval Results (legacy)
Instructions to use fwizzer1/Fwizzer-R1-3B-EN-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-EN-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-EN-v2 # Run inference directly in the terminal: llama cli -hf fwizzer1/Fwizzer-R1-3B-EN-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-EN-v2 # Run inference directly in the terminal: llama cli -hf fwizzer1/Fwizzer-R1-3B-EN-v2
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-EN-v2 # Run inference directly in the terminal: ./llama-cli -hf fwizzer1/Fwizzer-R1-3B-EN-v2
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-EN-v2 # Run inference directly in the terminal: ./build/bin/llama-cli -hf fwizzer1/Fwizzer-R1-3B-EN-v2
Use Docker
docker model run hf.co/fwizzer1/Fwizzer-R1-3B-EN-v2
- LM Studio
- Jan
- vLLM
How to use fwizzer1/Fwizzer-R1-3B-EN-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-EN-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-EN-v2", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/fwizzer1/Fwizzer-R1-3B-EN-v2
- Ollama
How to use fwizzer1/Fwizzer-R1-3B-EN-v2 with Ollama:
ollama run hf.co/fwizzer1/Fwizzer-R1-3B-EN-v2
- Unsloth Desktop
- Docker Model Runner
How to use fwizzer1/Fwizzer-R1-3B-EN-v2 with Docker Model Runner:
docker model run hf.co/fwizzer1/Fwizzer-R1-3B-EN-v2
- Lemonade
How to use fwizzer1/Fwizzer-R1-3B-EN-v2 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull fwizzer1/Fwizzer-R1-3B-EN-v2
Run and chat with the model
lemonade run user.Fwizzer-R1-3B-EN-v2-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
Commit History
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Fix Fwizzer-R1.preset.json encoding, system prompt, and reasoning parser
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Fix chat template: remove <think> prefill for automatic UI accordion/reasoning curtain
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Copy files from models/fwizzer1/Fwizzer-R1-3B-v2
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Update comprehensive flagship Model Card (EN-v2)
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Add generation_config.json with optimal sampling defaults
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Add Jan desktop model configuration
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Add Ollama Modelfile with baked-in reasoning and system prompt
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Sync tokenizer.json from fwizzer1/Fwizzer-R1-3B-v2
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Clean up debug log
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Update .gitattributes with LFS rules for tokenizer.json and gguf
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Add tokenizer_config.json
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Add Fwizzer-R1.preset.json
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Add Jan desktop model configuration
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Add Ollama Modelfile
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Add rich Model Card with all platform guides
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Sync chat_template.jinja from fwizzer1/Fwizzer-R1-3B-v2
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Upload kaggle_debug_error.log with huggingface_hub
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initial commit
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