Instructions to use Felladrin/gguf-sharded-Qwen2-1.5B-Instruct-imat 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 Felladrin/gguf-sharded-Qwen2-1.5B-Instruct-imat 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 Felladrin/gguf-sharded-Qwen2-1.5B-Instruct-imat:Q5_K_M # Run inference directly in the terminal: llama cli -hf Felladrin/gguf-sharded-Qwen2-1.5B-Instruct-imat:Q5_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Felladrin/gguf-sharded-Qwen2-1.5B-Instruct-imat:Q5_K_M # Run inference directly in the terminal: llama cli -hf Felladrin/gguf-sharded-Qwen2-1.5B-Instruct-imat:Q5_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 Felladrin/gguf-sharded-Qwen2-1.5B-Instruct-imat:Q5_K_M # Run inference directly in the terminal: ./llama-cli -hf Felladrin/gguf-sharded-Qwen2-1.5B-Instruct-imat:Q5_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 Felladrin/gguf-sharded-Qwen2-1.5B-Instruct-imat:Q5_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Felladrin/gguf-sharded-Qwen2-1.5B-Instruct-imat:Q5_K_M
Use Docker
docker model run hf.co/Felladrin/gguf-sharded-Qwen2-1.5B-Instruct-imat:Q5_K_M
- LM Studio
- Jan
- vLLM
How to use Felladrin/gguf-sharded-Qwen2-1.5B-Instruct-imat with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Felladrin/gguf-sharded-Qwen2-1.5B-Instruct-imat" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Felladrin/gguf-sharded-Qwen2-1.5B-Instruct-imat", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Felladrin/gguf-sharded-Qwen2-1.5B-Instruct-imat:Q5_K_M
- Ollama
How to use Felladrin/gguf-sharded-Qwen2-1.5B-Instruct-imat with Ollama:
ollama run hf.co/Felladrin/gguf-sharded-Qwen2-1.5B-Instruct-imat:Q5_K_M
- Unsloth Desktop
- Docker Model Runner
How to use Felladrin/gguf-sharded-Qwen2-1.5B-Instruct-imat with Docker Model Runner:
docker model run hf.co/Felladrin/gguf-sharded-Qwen2-1.5B-Instruct-imat:Q5_K_M
- Lemonade
How to use Felladrin/gguf-sharded-Qwen2-1.5B-Instruct-imat with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Felladrin/gguf-sharded-Qwen2-1.5B-Instruct-imat:Q5_K_M
Run and chat with the model
lemonade run user.gguf-sharded-Qwen2-1.5B-Instruct-imat-Q5_K_M
List all available models
lemonade list
- Atomic Chat
Download qwen2-1-00014-of-00022.gguf from Felladrin/gguf-sharded-Qwen2-1.5B-Instruct-imat: direct link, hf CLI and curl.
- Browser
- Download file 42 MB
-
https://huggingface.co/Felladrin/gguf-sharded-Qwen2-1.5B-Instruct-imat/resolve/main/qwen2-1-00014-of-00022.gguf
- Command line
-
hf download hf://Felladrin/gguf-sharded-Qwen2-1.5B-Instruct-imat/qwen2-1-00014-of-00022.gguf
-
curl -L -o qwen2-1-00014-of-00022.gguf https://huggingface.co/Felladrin/gguf-sharded-Qwen2-1.5B-Instruct-imat/resolve/main/qwen2-1-00014-of-00022.gguf
42 MB
- Xet hash:
- c0f02930104fcd69fc01e6430d0f95d5de8adb64587c47dbe6adca34fb4908c3
- Size of remote file:
- 42 MB
- SHA256:
- c211da877e9f120111ef48fac1f6c9b6e911df2592e63381f32f41fb69130345
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