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b2b054d
1
Parent(s):
5f3bbeb
make it work please
Browse files- app.py +5 -3
- requirements.txt +1 -4
app.py
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@@ -2,9 +2,11 @@ import gradio as gr
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import matplotlib.pyplot as plt
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from transformers import pipeline
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# Load the Hugging Face
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translator = pipeline("translation", model="Helsinki-NLP/opus-mt-en-es")
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# Define the function to generate the graph based on the translated prompt
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def generate_graph(prompt):
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@@ -12,7 +14,7 @@ def generate_graph(prompt):
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translated_prompt = translator(prompt, max_length=100, src_lang="en", tgt_lang="es")
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translated_text = translated_prompt[0]['translation_text']
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# Generate text using the Hugging Face pipeline
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response = generator(translated_text, max_length=100)
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text = response[0]['generated_text']
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import matplotlib.pyplot as plt
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from transformers import pipeline
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# Load the Hugging Face pipeline for translation
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translator = pipeline("translation", model="Helsinki-NLP/opus-mt-en-es")
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# Load the Hugging Face pipeline for text generation using GPT-J
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generator = pipeline("text-generation", model="EleutherAI/gpt-j-6B")
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# Define the function to generate the graph based on the translated prompt
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def generate_graph(prompt):
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translated_prompt = translator(prompt, max_length=100, src_lang="en", tgt_lang="es")
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translated_text = translated_prompt[0]['translation_text']
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# Generate text using the Hugging Face pipeline with GPT-J
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response = generator(translated_text, max_length=100)
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text = response[0]['generated_text']
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requirements.txt
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@@ -1,6 +1,3 @@
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gradio
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matplotlib
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transformers
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sentencepiece
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torch
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tensorflow
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gradio
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matplotlib
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transformers
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