Instructions to use xsharp/deepseek_sql_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xsharp/deepseek_sql_model with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("xsharp/deepseek_sql_model", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use xsharp/deepseek_sql_model 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 xsharp/deepseek_sql_model 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 xsharp/deepseek_sql_model to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for xsharp/deepseek_sql_model to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="xsharp/deepseek_sql_model", max_seq_length=2048, )
- Xet hash:
- a72bf15a6916e1137c294971c369b2e3c82dedc56314f4fb7977c9f81b34f419
- Size of remote file:
- 168 MB
- SHA256:
- 445faafb23a0fbd2190a9a2d3b9d0897dd2203b9bc4d19fe041ddc4c9a58349d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.