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README.md
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<question>{question}</question>
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<sql>"""
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```
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```python
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from transformers import AutoModelForCasualLM, AutoTokenizer
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outputs = model.generate(**inputs, max_new_tokens=200)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True).split('<sql>')[1].split('</sql>')[0])
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```
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## The PipableAI team
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<question>{question}</question>
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<sql>"""
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```
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+
pytorch
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```python
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from transformers import AutoModelForCasualLM, AutoTokenizer
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outputs = model.generate(**inputs, max_new_tokens=200)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True).split('<sql>')[1].split('</sql>')[0])
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```
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flax
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```python
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from transformers import AutoModelForCasualLM, AutoTokenizer
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device = "cuda"
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model = FlaxAutoModelForCausalLM.from_pretrained("PipableAI/pipSQL1b" , from_pt=True)
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tokenizer = AutoTokenizer.from_pretrained("PipableAI/pipSQL1b")
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```
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## The PipableAI team
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