Instructions to use eliza555beth2002/DeepSeek-R1-Distill-Text2SQL-Overtrained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eliza555beth2002/DeepSeek-R1-Distill-Text2SQL-Overtrained with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("eliza555beth2002/DeepSeek-R1-Distill-Text2SQL-Overtrained", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use eliza555beth2002/DeepSeek-R1-Distill-Text2SQL-Overtrained 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 eliza555beth2002/DeepSeek-R1-Distill-Text2SQL-Overtrained 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 eliza555beth2002/DeepSeek-R1-Distill-Text2SQL-Overtrained to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for eliza555beth2002/DeepSeek-R1-Distill-Text2SQL-Overtrained to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="eliza555beth2002/DeepSeek-R1-Distill-Text2SQL-Overtrained", max_seq_length=2048, )
- Xet hash:
- 1061508873a316d1be50a248348dec80c60a9b4878d0ceb4ed394706067dad22
- Size of remote file:
- 17.2 MB
- SHA256:
- 26c881aaf4ef935b1516ec79ad6405dd2a459f2b5d431a8a4a1399c92f3ba022
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