Instructions to use MrezaPRZ/sql-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MrezaPRZ/sql-encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MrezaPRZ/sql-encoder")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MrezaPRZ/sql-encoder") model = AutoModelForSequenceClassification.from_pretrained("MrezaPRZ/sql-encoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tmp-checkpoint-40/model.safetensors from MrezaPRZ/sql-encoder: direct link, hf CLI and curl.
- Browser
- Download file 2.56 GB
-
https://huggingface.co/MrezaPRZ/sql-encoder/resolve/main/tmp-checkpoint-40/model.safetensors
- Command line
-
hf download hf://MrezaPRZ/sql-encoder/tmp-checkpoint-40/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/MrezaPRZ/sql-encoder/resolve/main/tmp-checkpoint-40/model.safetensors
2.56 GB
- Xet hash:
- 6afafc16332ef4caaf6127fd26428025f4f421fdb5e18ee77e1020447e6bf11c
- Size of remote file:
- 2.56 GB
- SHA256:
- 40838fa9193ac8f3172c2b0711af6c006d3359e781d9e72e3314cb6b99e39790
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