Upload 4 files
Browse files- nlp/sql_model.py +4 -2
nlp/sql_model.py
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# from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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from transformers import AutoTokenizer, AutoModelForCausalLM
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class SQLModel:
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def __init__(self, model_name="google/flan-t5-base"):
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# self.tokenizer = AutoTokenizer.from_pretrained(model_name)
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# self.model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
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self.
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def generate_sql(self, natural_language_query):
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input_text = f"""You are a highly skilled SQL translator. Your task is to convert natural language descriptions of data queries into correct and optimized SQL statements.
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# from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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import os
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from transformers import AutoTokenizer, AutoModelForCausalLM
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class SQLModel:
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def __init__(self, model_name="google/flan-t5-base"):
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# self.tokenizer = AutoTokenizer.from_pretrained(model_name)
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# self.model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
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hf_token = os.environ.get("HF_HUB_TOKEN")
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self.tokenizer = AutoTokenizer.from_pretrained("google/gemma-7b-it",use_auth_token=hf_token)
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self.model = AutoModelForCausalLM.from_pretrained("google/gemma-7b-it",use_auth_token=hf_token)
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def generate_sql(self, natural_language_query):
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input_text = f"""You are a highly skilled SQL translator. Your task is to convert natural language descriptions of data queries into correct and optimized SQL statements.
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