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")# 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
File size: 462 Bytes
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"bos_token": {
"content": "<|begin▁of▁sentence|>",
"lstrip": false,
"normalized": true,
"rstrip": false,
"single_word": false
},
"eos_token": {
"content": "<|EOT|>",
"lstrip": false,
"normalized": true,
"rstrip": false,
"single_word": false
},
"pad_token": {
"content": "<|end▁of▁sentence|>",
"lstrip": false,
"normalized": true,
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"single_word": false
}
}
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