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Update app.py
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app.py
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from huggingface_hub import InferenceClient
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import gradio as gr
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# Initialize the inference client with the Mixtral model
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client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
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def translate_text(
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prompt =
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#
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inputs=prompt,
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parameters={"max_new_tokens": 100},
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options={"wait_for_model": True}
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)
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# Extract the translated text from the response
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translated_text = response[0]['generated_text']
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#
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return translated_text
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languages = [
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"French",
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"Spanish",
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"German",
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"Italian",
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"Portuguese",
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# Add more languages as needed
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]
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iface = gr.Interface(
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fn=translate_text,
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inputs=[
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gr.Textbox(label="Text to Translate", placeholder="Enter text here..."),
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gr.
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],
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outputs=gr.Textbox(label="Translated Text"),
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title="Simple Translator with Mixtral",
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description="Translate text to
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)
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iface.launch()
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from huggingface_hub import InferenceClient
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import gradio as gr
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client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
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def translate_text(input_text, target_language):
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prompt = f"Translate the following text into {target_language}: {input_text}"
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response = client.text_generation(prompt, parameters={"max_new_tokens": 256}, options={"wait_for_model": True})
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# Since the model's response includes the prompt, we extract only the translated text
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# Assuming the translated text follows immediately after the prompt
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translated_text = response[0]['generated_text']
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# Clean the response to display only the translated part
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# This might need to be adjusted based on how the model includes the prompt in its response
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clean_translation = translated_text[len(prompt):].strip()
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return clean_translation
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iface = gr.Interface(
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fn=translate_text,
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inputs=[
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gr.Textbox(label="Text to Translate", placeholder="Enter the text you want to translate here..."),
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gr.Textbox(label="Target Language", placeholder="Enter the target language (e.g., French, Spanish)..."),
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],
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outputs=gr.Textbox(label="Translated Text"),
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title="Simple Translator with Mixtral",
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description="Translate text to your specified language using the Mixtral model from Hugging Face."
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)
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iface.launch()
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