update all
Browse files- app.py +5 -2
- language.py +3 -4
- requirements.txt +4 -3
- text-to-speach.py +19 -0
app.py
CHANGED
@@ -1,6 +1,8 @@
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from image import *
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from language import *
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import streamlit as st
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# url = "https://i.imgur.com/qs0CxjE_d.webp?maxwidth=760&fidelity=grand"
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@@ -14,8 +16,9 @@ url = st.text_input('mettez le liens de votre image')
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if st.button('générer'):
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responseBase = image(url, question)
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st.write('response is :', responseBase)
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st.write('Part 2')
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print(question)
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st.write(longText(responseBase, question))
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print(
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from image import *
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from language import *
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from translation import *
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import streamlit as st
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import os
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# url = "https://i.imgur.com/qs0CxjE_d.webp?maxwidth=760&fidelity=grand"
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if st.button('générer'):
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responseBase = image(url, question)
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st.write('response is :', responseBase)
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st.write('Part 2')
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st.write(longText(responseBase, question))
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print("####TEST TTS####")
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os.system("text-to-speach.py")
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language.py
CHANGED
@@ -3,12 +3,11 @@ from transformers import T5Tokenizer, T5ForConditionalGeneration
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def longText(answere, question):
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print('###### LANGUAGES ######')
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input_text = "
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tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-large")
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model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-large")
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input_ids = tokenizer(input_text, return_tensors="pt").input_ids
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outputs = model.generate(input_ids)
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print(tokenizer.decode(outputs[0]))
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return tokenizer.decode(outputs[0]).replace("<pad>","").replace("</s>","")
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def longText(answere, question):
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print('###### LANGUAGES ######')
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input_text = "i have a question and answer.\nthe question is : {}\n the response is : {}\n with this information, can you create an answer phrase?".format(question, answere)
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tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-large")
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model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-large", device_map="auto")
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input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to("cuda")
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outputs = model.generate(input_ids)
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return tokenizer.decode(outputs[0]).replace("<pad>","").replace("</s>","")
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requirements.txt
CHANGED
@@ -1,4 +1,5 @@
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transformers[torch]
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-
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-
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transformers[torch]
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sacremoses
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bark
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scipy
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IPython
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text-to-speach.py
ADDED
@@ -0,0 +1,19 @@
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from bark import SAMPLE_RATE, generate_audio, preload_models
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from scipy.io.wavfile import write as write_wav
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from IPython.display import Audio
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# download and load all models
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preload_models()
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# generate audio from text
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text_prompt = """
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Hello, my name is Suno. And, uh — and I like pizza. [laughs]
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But I also have other interests such as playing tic tac toe.
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"""
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audio_array = generate_audio(text_prompt)
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# save audio to disk
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write_wav("bark_generation.wav", SAMPLE_RATE, audio_array)
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# play text in notebook
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Audio(audio_array, rate=SAMPLE_RATE)
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