Instructions to use ViorikaAI-org/CalmaCatCoder-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-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-GGUF:F16 # Run inference directly in the terminal: llama cli -hf ViorikaAI-org/CalmaCatCoder-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-GGUF:F16 # Run inference directly in the terminal: llama cli -hf ViorikaAI-org/CalmaCatCoder-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-GGUF:F16 # Run inference directly in the terminal: ./llama-cli -hf ViorikaAI-org/CalmaCatCoder-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-GGUF:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf ViorikaAI-org/CalmaCatCoder-GGUF:F16
Use Docker
docker model run hf.co/ViorikaAI-org/CalmaCatCoder-GGUF:F16
- LM Studio
- Jan
- vLLM
How to use ViorikaAI-org/CalmaCatCoder-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-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-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/ViorikaAI-org/CalmaCatCoder-GGUF:F16
- Ollama
How to use ViorikaAI-org/CalmaCatCoder-GGUF with Ollama:
ollama run hf.co/ViorikaAI-org/CalmaCatCoder-GGUF:F16
- Unsloth Desktop
- Docker Model Runner
How to use ViorikaAI-org/CalmaCatCoder-GGUF with Docker Model Runner:
docker model run hf.co/ViorikaAI-org/CalmaCatCoder-GGUF:F16
- Lemonade
How to use ViorikaAI-org/CalmaCatCoder-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull ViorikaAI-org/CalmaCatCoder-GGUF:F16
Run and chat with the model
lemonade run user.CalmaCatCoder-GGUF-F16
List all available models
lemonade list
- Atomic Chat
Update README.md
Browse files
README.md
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---
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license: other
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license_name: ccpl-1
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license_link: LICENSE
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---
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license: other
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license_name: ccpl-1.0
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license_link: LICENSE
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language:
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- en
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- ru
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pipeline_tag: text-generation
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tags:
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- code
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- qwen2
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- gguf
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- llama-cpp
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- 280m
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base_model:
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- ViorikaAI-org/CalmaCatCoder
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---
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# CalmaCatCoder-280M (GGUF)
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**CalmaCatCoder-280M** is a compact and ultra-fast 280M language model trained from scratch for Python code generation.
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This repository contains quantized **GGUF** weights optimized for `llama.cpp`, Ollama, LM Studio, and CPU/GPU edge inference.
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---
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## ⚡ Specs
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* **Architecture:** Transformer / Causal LM (Qwen2-like)
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* **Parameters:** ~280M
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* **Format:** GGUF
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* **Prompt Format:** ChatML
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---
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## 🔗 Original Weights
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For PyTorch / SafeTensors base weights and fine-tuning:
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👉 **Original Repository:** [ViorikaAI/CalmaCatCoder](https://huggingface.co/ViorikaAI/CalmaCatCoder)
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---
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## 📜 License
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Distributed under the **CalmaCat Public License (CCPL-1.0)**. See [LICENSE](./LICENSE) for details.
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---
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<details>
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<summary><b>🇷🇺 Нажмите, чтобы открыть описание на русском языке (Click to expand Russian description)</b></summary>
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<br>
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# CalmaCatCoder-280M (GGUF)
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**CalmaCatCoder-280M** — компактная и ультрабыстрая языковая модель на 280 млн параметров, обученная с нуля для генерации кода на Python.
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В этом репозитории находятся квантованные **GGUF** веса, оптимизированные для работы через `llama.cpp`, Ollama, LM Studio и быстрой работы на CPU/GPU.
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---
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## ⚡ Характеристики
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* **Архитектура:** Transformer / Causal LM (Qwen2-like)
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* **Объём параметров:** ~280 млн
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* **Формат:** GGUF
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* **Формат диалога:** ChatML
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---
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## 🔗 Оригинальные веса
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Если вам нужны исходные веса в формате PyTorch / SafeTensors для дообучения:
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👉 **Основной репозиторий:** [ViorikaAI/CalmaCatCoder](https://huggingface.co/ViorikaAI/CalmaCatCoder)
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---
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## 📜 Лицензия
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Распространяется под кастомной открытой лицензией **CalmaCat Public License (CCPL-1.0)**.
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Полный текст см. в файле [LICENSE](./LICENSE).
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</details>
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