Instructions to use hdv250202/qwen2.5_1.5b_text2sql_unsloth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hdv250202/qwen2.5_1.5b_text2sql_unsloth with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("hdv250202/qwen2.5_1.5b_text2sql_unsloth", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use hdv250202/qwen2.5_1.5b_text2sql_unsloth 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 hdv250202/qwen2.5_1.5b_text2sql_unsloth:F16 # Run inference directly in the terminal: llama cli -hf hdv250202/qwen2.5_1.5b_text2sql_unsloth:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf hdv250202/qwen2.5_1.5b_text2sql_unsloth:F16 # Run inference directly in the terminal: llama cli -hf hdv250202/qwen2.5_1.5b_text2sql_unsloth: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 hdv250202/qwen2.5_1.5b_text2sql_unsloth:F16 # Run inference directly in the terminal: ./llama-cli -hf hdv250202/qwen2.5_1.5b_text2sql_unsloth: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 hdv250202/qwen2.5_1.5b_text2sql_unsloth:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf hdv250202/qwen2.5_1.5b_text2sql_unsloth:F16
Use Docker
docker model run hf.co/hdv250202/qwen2.5_1.5b_text2sql_unsloth:F16
- LM Studio
- Jan
- Ollama
How to use hdv250202/qwen2.5_1.5b_text2sql_unsloth with Ollama:
ollama run hf.co/hdv250202/qwen2.5_1.5b_text2sql_unsloth:F16
- Unsloth Desktop
- Docker Model Runner
How to use hdv250202/qwen2.5_1.5b_text2sql_unsloth with Docker Model Runner:
docker model run hf.co/hdv250202/qwen2.5_1.5b_text2sql_unsloth:F16
- Lemonade
How to use hdv250202/qwen2.5_1.5b_text2sql_unsloth with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull hdv250202/qwen2.5_1.5b_text2sql_unsloth:F16
Run and chat with the model
lemonade run user.qwen2.5_1.5b_text2sql_unsloth-F16
List all available models
lemonade list
- Atomic Chat
Download unsloth.F16.gguf from hdv250202/qwen2.5_1.5b_text2sql_unsloth: direct link, hf CLI and curl.
- Browser
- Download file 3.09 GB
-
https://huggingface.co/hdv250202/qwen2.5_1.5b_text2sql_unsloth/resolve/main/unsloth.F16.gguf
- Command line
-
hf download hf://hdv250202/qwen2.5_1.5b_text2sql_unsloth/unsloth.F16.gguf
-
curl -L -o unsloth.F16.gguf https://huggingface.co/hdv250202/qwen2.5_1.5b_text2sql_unsloth/resolve/main/unsloth.F16.gguf
3.09 GB
- Xet hash:
- d6ac17b4275faf030d985f88eef97f9a01aa814f6c63d994ac9e5562b6e190d3
- Size of remote file:
- 3.09 GB
- SHA256:
- 6801587fd730627ffe02ce0c847ef78d137c1aeca9904df0e5fb344229a7650d
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