Instructions to use gai-labs/strela-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use gai-labs/strela-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="gai-labs/strela-GGUF", filename="strela-q2_k.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use gai-labs/strela-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 gai-labs/strela-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf gai-labs/strela-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf gai-labs/strela-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf gai-labs/strela-GGUF:Q4_K_M
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 gai-labs/strela-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf gai-labs/strela-GGUF:Q4_K_M
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 gai-labs/strela-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf gai-labs/strela-GGUF:Q4_K_M
Use Docker
docker model run hf.co/gai-labs/strela-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use gai-labs/strela-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "gai-labs/strela-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "gai-labs/strela-GGUF", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/gai-labs/strela-GGUF:Q4_K_M
- Ollama
How to use gai-labs/strela-GGUF with Ollama:
ollama run hf.co/gai-labs/strela-GGUF:Q4_K_M
- Unsloth Studio
How to use gai-labs/strela-GGUF with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for gai-labs/strela-GGUF to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for gai-labs/strela-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for gai-labs/strela-GGUF to start chatting
- Atomic Chat new
- Docker Model Runner
How to use gai-labs/strela-GGUF with Docker Model Runner:
docker model run hf.co/gai-labs/strela-GGUF:Q4_K_M
- Lemonade
How to use gai-labs/strela-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull gai-labs/strela-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.strela-GGUF-Q4_K_M
List all available models
lemonade list
GGUF версия стрелы.
| Файл | Токенов/Секунда* | Скорость | Качество | Описание |
|---|---|---|---|---|
| strela-q8_0.gguf | 5 | Медленная | Отличное | Лучше всего подходит для Cuda |
| strela-q4_k_m.gguf | 9 | Средняя | Хорошое | Отлично работает на CPU, рекомендуется для использования на слабых устройствах |
| strela-q2_k.gguf | 13 | Быстрая | Плохое | Использовать только для английского языка с задачей, связанной с русскими словами |
*Протестированно на Intel(R) Core(TM) i5-10300H CPU @ 2.50GHz
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