Instructions to use tensorblock/Qwen2-1.5B-Instruct-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tensorblock/Qwen2-1.5B-Instruct-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("tensorblock/Qwen2-1.5B-Instruct-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use tensorblock/Qwen2-1.5B-Instruct-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 tensorblock/Qwen2-1.5B-Instruct-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf tensorblock/Qwen2-1.5B-Instruct-GGUF:Q2_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf tensorblock/Qwen2-1.5B-Instruct-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf tensorblock/Qwen2-1.5B-Instruct-GGUF:Q2_K
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 tensorblock/Qwen2-1.5B-Instruct-GGUF:Q2_K # Run inference directly in the terminal: ./llama-cli -hf tensorblock/Qwen2-1.5B-Instruct-GGUF:Q2_K
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 tensorblock/Qwen2-1.5B-Instruct-GGUF:Q2_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf tensorblock/Qwen2-1.5B-Instruct-GGUF:Q2_K
Use Docker
docker model run hf.co/tensorblock/Qwen2-1.5B-Instruct-GGUF:Q2_K
- LM Studio
- Jan
- Ollama
How to use tensorblock/Qwen2-1.5B-Instruct-GGUF with Ollama:
ollama run hf.co/tensorblock/Qwen2-1.5B-Instruct-GGUF:Q2_K
- Unsloth Desktop
- Docker Model Runner
How to use tensorblock/Qwen2-1.5B-Instruct-GGUF with Docker Model Runner:
docker model run hf.co/tensorblock/Qwen2-1.5B-Instruct-GGUF:Q2_K
- Lemonade
How to use tensorblock/Qwen2-1.5B-Instruct-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tensorblock/Qwen2-1.5B-Instruct-GGUF:Q2_K
Run and chat with the model
lemonade run user.Qwen2-1.5B-Instruct-GGUF-Q2_K
List all available models
lemonade list
- Atomic Chat
- Xet hash:
- 8052292f84cd346227fc9c792790a4ddbf60e9066074ba163b001579ac5bb96b
- Size of remote file:
- 986 MB
- SHA256:
- 17149c4019fe23c0611aa0b856d5c1a839040e31ffc23068782b0dbecbd111c2
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