Instructions to use ViorikaAI-org/CalmaCatCoder-next-mini-gguf 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 ViorikaAI-org/CalmaCatCoder-next-mini-gguf 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 ViorikaAI-org/CalmaCatCoder-next-mini-gguf:F16 # Run inference directly in the terminal: llama cli -hf ViorikaAI-org/CalmaCatCoder-next-mini-gguf:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf ViorikaAI-org/CalmaCatCoder-next-mini-gguf:F16 # Run inference directly in the terminal: llama cli -hf ViorikaAI-org/CalmaCatCoder-next-mini-gguf: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 ViorikaAI-org/CalmaCatCoder-next-mini-gguf:F16 # Run inference directly in the terminal: ./llama-cli -hf ViorikaAI-org/CalmaCatCoder-next-mini-gguf: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 ViorikaAI-org/CalmaCatCoder-next-mini-gguf:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf ViorikaAI-org/CalmaCatCoder-next-mini-gguf:F16
Use Docker
docker model run hf.co/ViorikaAI-org/CalmaCatCoder-next-mini-gguf:F16
- LM Studio
- Jan
- vLLM
How to use ViorikaAI-org/CalmaCatCoder-next-mini-gguf with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ViorikaAI-org/CalmaCatCoder-next-mini-gguf" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ViorikaAI-org/CalmaCatCoder-next-mini-gguf", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/ViorikaAI-org/CalmaCatCoder-next-mini-gguf:F16
- Ollama
How to use ViorikaAI-org/CalmaCatCoder-next-mini-gguf with Ollama:
ollama run hf.co/ViorikaAI-org/CalmaCatCoder-next-mini-gguf:F16
- Unsloth Desktop
- Docker Model Runner
How to use ViorikaAI-org/CalmaCatCoder-next-mini-gguf with Docker Model Runner:
docker model run hf.co/ViorikaAI-org/CalmaCatCoder-next-mini-gguf:F16
- Lemonade
How to use ViorikaAI-org/CalmaCatCoder-next-mini-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull ViorikaAI-org/CalmaCatCoder-next-mini-gguf:F16
Run and chat with the model
lemonade run user.CalmaCatCoder-next-mini-gguf-F16
List all available models
lemonade list
- Atomic Chat
Main repo:
GGUF / llama.cpp
The tokenizer has no BPE merges and a pre-tokenizer unknown to the stock converter, so
convert_hf_to_gguf.py fails on it. The make_gguf.py wrapper from the code repository patches this
at conversion time without modifying llama.cpp (details in its header):
git clone https://github.com/ggml-org/llama.cpp
python make_gguf.py llama.cpp CalmaCatCoder-Next-mini calmacatcoder-f16.gguf f16 # or q8_0
Because <|im_end|> is plain text, llama.cpp does not stop on it by itself. Save the ChatML prompt to a file
and use a reverse prompt:
llama-completion -m calmacatcoder-f16.gguf -no-cnv --no-escape -f prompt.txt -r "<|im_end|>" -n 300 --temp 0.7 --top-k 40
A warning special_eos_id is not in special_eog_ids is expected: the model has no EOS token.
Prefer f16/bf16 or q8_0; this model is so small that aggressive quantization will likely hurt it.
- Downloads last month
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16-bit
Model tree for ViorikaAI-org/CalmaCatCoder-next-mini-gguf
Base model
ViorikaAI-org/CalmaCatCoder-Next-mini