---
library_name: transformers
tags:
- Indian-Nuance
license: apache-2.0
datasets:
- ombhojane/smile-india
language:
- en
- hi
base_model:
- Qwen/Qwen2.5-1.5B-Instruct
pipeline_tag: text-generation
---

# SMILE for India!

Smile model nderstands the indian nunaces & give more accurate responses wrt. indian context


## Model Details

### Model Description

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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

- **Developed by:** 
- **Funded by [optional]:** https://github.com/ombhojane
- **Model type:** Quantized
- **Language(s) (NLP):** Python, Unsloth
- **License:** MIT
- **Finetuned from model [optional]:** Qwen/Qwen2.5-1.5B-Instruct

### Model Sources [optional]

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- **Repository:** https://github.com/ombhojane/smile
- **Paper [optional]:** On it, buildin'
- **Demo [optional]:** https://smilecrm.vercel.app/

<!-- ## Uses
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<!-- ### Direct Use
 -->
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
```
<!-- from transformers import pipeline
import torch

messages = [
    {"role": "user", "content": "give indian tadka ingrediants"}
]

# Use the GPU if available
device = 0 if torch.cuda.is_available() else -1
pipe = pipeline("text-generation", model="ombhojane/smile-small", device=device)

# Generate longer output text
generated_text = pipe(messages, max_new_tokens=200, num_return_sequences=1)
print(generated_text)

```
```
generated_text[0]['generated_text'][1]['content']
```
 -->
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<!-- ### Downstream Use [optional]
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### Out-of-Scope Use
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## Bias, Risks, and Limitations

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Parent model is equivalent to a SLM - might lags in some speacial areas

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## Training Details

### Training Data

https://huggingface.co/datasets/ombhojane/smile-india

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#### Training Hyperparameters

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## Evaluation
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### Results

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#### Summary

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## Environmental Impact
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## Technical Specifications [optional]

### Model Architecture and Objective

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#### Hardware

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#### Software

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