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README.md
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@@ -3,6 +3,31 @@ library_name: transformers
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tags: []
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---
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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tags: []
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---
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#Getting started
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!pip install transformers
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from transformers import T5ForConditionalGeneration, T5Tokenizer
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# Load the model and tokenizer from the directory where they are saved
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model = T5ForConditionalGeneration.from_pretrained('abhibheema/T5Validation')
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tokenizer = T5Tokenizer.from_pretrained('abhibheema/T5Validation')
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sample_input = """input text"""
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input_ids = tokenizer.encode(sample_input, return_tensors="pt")
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# Generate output
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with torch.no_grad():
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output_ids = model.generate(input_ids, max_new_tokens=512)
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output_text = tokenizer.decode(output_ids[0], skip_special_tokens=True)
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# Print the result
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print("Generated Output:", output_text)
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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