Instructions to use SivilTaram/poet-sql with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SivilTaram/poet-sql with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="SivilTaram/poet-sql")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SivilTaram/poet-sql") model = AutoModel.from_pretrained("SivilTaram/poet-sql", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from SivilTaram/poet-sql: direct link, hf CLI and curl.
- Browser
- Download file 1.36 MB
-
https://huggingface.co/SivilTaram/poet-sql/resolve/main/tokenizer.json
- Command line
-
hf download hf://SivilTaram/poet-sql/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/SivilTaram/poet-sql/resolve/main/tokenizer.json
1.36 MB
File too large to display, you can check the raw version instead.