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README.md
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---
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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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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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[More Information Needed]
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[More Information Needed]
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### Training Procedure
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---
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library_name: transformers
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tags:
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- Indian-Nuance
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license: apache-2.0
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datasets:
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- ombhojane/smile-india
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language:
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- en
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- hi
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base_model:
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- Qwen/Qwen2.5-1.5B-Instruct
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pipeline_tag: text-generation
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---
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# Model Card for Model ID
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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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```
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from transformers import pipeline
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import torch
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messages = [
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{"role": "user", "content": "give indian tadka ingrediants"}
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]
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# Use the GPU if available
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device = 0 if torch.cuda.is_available() else -1
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pipe = pipeline("text-generation", model="ombhojane/smile-small", device=device)
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# Generate longer output text
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generated_text = pipe(messages, max_new_tokens=200, num_return_sequences=1)
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print(generated_text)
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```
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```
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generated_text[0]['generated_text'][1]['content']
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```
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[More Information Needed]
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[More Information Needed]
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### Training Procedure
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