Uploading food not food text classifier demo app.py

.gitignore

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+script.py

README.md

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+# Whisper Small Tamil - Hugging Face Demo
+
+This repository hosts a demo for the **Whisper Small Tamil** model, fine-tuned for Tamil speech recognition. This model is based on OpenAI's Whisper-Small and has been trained to improve Automatic Speech Recognition (ASR) for Tamil language inputs.
+
+## 🚀 Demo
+Try the model directly on [🤗 Hugging Face Spaces](https://huggingface.co/spaces/deepakkumar07/whisper-small-tamil).
+
+## 📝 Model Details
+- **Base Model:** OpenAI Whisper-Small
+- **Fine-tuned for:** Tamil ASR
+- **Dataset Used:** Common Voice Tamil & other curated datasets
+- **Supports:** Tamil speech-to-text transcription
+
+## 🔧 How to Use
+You can use this model in Python with the `transformers` library:
+
+```python
+from transformers import pipeline
+
+# Load model from Hugging Face Hub
+asr_pipeline = pipeline("automatic-speech-recognition", model="deepakkumar07/whisper-small-tamil")
+
+# Transcribe an audio file
+result = asr_pipeline("path/to/audio.wav")
+print(result["text"])
+```
+
+## 📊 Performance
+This model is optimized for Tamil speech but may still have minor errors in transcription, especially with noisy audio or mixed-language inputs. Contributions and improvements are welcome!
+
+## 📌 Training Details
+- Fine-tuned using the **Hugging Face Transformers** and **datasets** libraries.
+- Trained on GPUs for better performance.
+- Supports **streaming inference** for real-time transcription.
+
+## 💡 Applications
+- Tamil voice-to-text conversion
+- Subtitling and transcription services
+- Voice-controlled Tamil applications
+
+## 🤝 Contributing
+If you find any issues or want to improve the model, feel free to open a PR or reach out!
+
+## 📜 License
+This model is released under an open license. Please refer to OpenAI's original Whisper license for base model terms.
+
 ---
-title: Whisper Small Tamil Demo
-emoji: 😻
-colorFrom: gray
-colorTo: red
-sdk: gradio
-sdk_version: 5.20.0
-app_file: app.py
-pinned: false
----
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+For more details, check out the [Hugging Face model page](https://huggingface.co/deepakkumar07/whisper-small-tamil). 🚀
+

app.py

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+from transformers import pipeline
+import gradio as gr
+
+pipe = pipeline(model="deepakkumar07/whisper-small-tamil")  # change to "your-username/the-name-you-picked"
+
+def transcribe(audio):
+    text = pipe(audio)["text"]
+    return text
+
+iface = gr.Interface(
+    fn=transcribe, 
+    inputs=gr.Audio(sources=["microphone", "upload"], type="filepath"), 
+    outputs="text",
+    title="Whisper Small Tamil",
+    description="Realtime demo for Tamil speech recognition using a fine-tuned Whisper small model.",
+)
+if __name__ == "__main__":
+    iface.launch()

requirements.txt

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+gradio
+torch
+transformers