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Update README.md

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@@ -7,9 +7,6 @@ base_model:
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  - Qwen/Qwen2.5-3B-Instruct
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  pipeline_tag: text-generation
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  ---
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-
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- # Model Card for Model ID
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-
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  # Fine-Tuned LLM for Text-to-SQL Conversion
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  This model is a fine-tuned version of [Qwen/Qwen2.5-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-3B-Instruct) designed to convert natural language queries into SQL statements. It was trained on the `gretelai/synthetic_text_to_sql` dataset and can provide both SQL queries and table schema context when needed.
@@ -44,8 +41,8 @@ To use the model for text-to-SQL conversion, you can load it using the `transfor
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  ```python
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  from transformers import AutoTokenizer, AutoModelForCausalLM
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- tokenizer = AutoTokenizer.from_pretrained("your-model-id")
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- model = AutoModelForCausalLM.from_pretrained("your-model-id")
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  # Input prompt
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  query = "What is the total number of hospital beds in each state?"
 
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  - Qwen/Qwen2.5-3B-Instruct
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  pipeline_tag: text-generation
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  ---
 
 
 
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  # Fine-Tuned LLM for Text-to-SQL Conversion
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  This model is a fine-tuned version of [Qwen/Qwen2.5-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-3B-Instruct) designed to convert natural language queries into SQL statements. It was trained on the `gretelai/synthetic_text_to_sql` dataset and can provide both SQL queries and table schema context when needed.
 
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  ```python
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  from transformers import AutoTokenizer, AutoModelForCausalLM
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+ tokenizer = AutoTokenizer.from_pretrained("Ellbendls/Qwen-2.5-3b-Text_to_SQL")
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+ model = AutoModelForCausalLM.from_pretrained("Ellbendls/Qwen-2.5-3b-Text_to_SQL")
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  # Input prompt
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  query = "What is the total number of hospital beds in each state?"