Spaces:
Sleeping
Sleeping
Create app.py
Browse files
app.py
ADDED
@@ -0,0 +1,57 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import gradio as gr
|
2 |
+
import whisper
|
3 |
+
from transformers import MBartForConditionalGeneration, MBart50TokenizerFast
|
4 |
+
|
5 |
+
# Cargar modelo Whisper y modelo de traducci贸n MBart
|
6 |
+
whisper_models = {
|
7 |
+
"tiny.en": whisper.load_model("tiny.en"),
|
8 |
+
"base.en": whisper.load_model("base.en"),
|
9 |
+
"small.en": whisper.load_model("small.en"),
|
10 |
+
"medium.en": whisper.load_model("medium.en"),
|
11 |
+
}
|
12 |
+
|
13 |
+
translation_model = MBartForConditionalGeneration.from_pretrained("SnypzZz/Llama2-13b-Language-translate")
|
14 |
+
translation_tokenizer = MBart50TokenizerFast.from_pretrained("SnypzZz/Llama2-13b-Language-translate", src_lang="en_XX")
|
15 |
+
|
16 |
+
# Funci贸n para transcribir el audio
|
17 |
+
def whisper_transcript(model_size, audio_file):
|
18 |
+
loaded_model = whisper_models[model_size]
|
19 |
+
transcript = loaded_model.transcribe(audio_file, language="english")
|
20 |
+
return transcript["text"]
|
21 |
+
|
22 |
+
# Funci贸n para traducir el texto
|
23 |
+
def translate_text(input_text, language_code):
|
24 |
+
model_inputs = translation_tokenizer(input_text, return_tensors="pt")
|
25 |
+
generated_tokens = translation_model.generate(
|
26 |
+
**model_inputs,
|
27 |
+
forced_bos_token_id=translation_tokenizer.lang_code_to_id[language_code]
|
28 |
+
)
|
29 |
+
output = translation_tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)[0]
|
30 |
+
return output.strip()
|
31 |
+
|
32 |
+
# Interfaz de Gradio combinada
|
33 |
+
with gr.Blocks(theme="Nymbo/Nymbo_Theme") as demo:
|
34 |
+
gr.Markdown("# Transcribe y Traduce Audios")
|
35 |
+
gr.Markdown("**C贸mo usar**: Selecciona un modelo de transcripci贸n, graba o sube un audio en ingl茅s y clica en transcribir. Luego, elige un idioma y traduce el texto.")
|
36 |
+
|
37 |
+
# Selecci贸n de modelo y entrada de audio
|
38 |
+
model_selector = gr.Dropdown(
|
39 |
+
label="Selecciona el modelo Whisper",
|
40 |
+
choices=["tiny.en", "base.en", "small.en", "medium.en"],
|
41 |
+
value="base.en",
|
42 |
+
)
|
43 |
+
audio_input = gr.Audio(label="Sube o graba el audio", source=["upload", "microphone"], type="filepath")
|
44 |
+
|
45 |
+
# Bot贸n para ejecutar transcripci贸n
|
46 |
+
transcript_output = gr.Textbox(label="Texto transcrito (ingl茅s)")
|
47 |
+
transcribe_button = gr.Button("Transcribir Audio")
|
48 |
+
transcribe_button.click(whisper_transcript, inputs=[model_selector, audio_input], outputs=transcript_output)
|
49 |
+
|
50 |
+
# Selecci贸n de idioma de traducci贸n y bot贸n de traducci贸n
|
51 |
+
language_selector = gr.Dropdown(["de_DE", "es_XX", "fr_XX", "sv_SE", "ru_RU"], label="Elige el idioma de salida")
|
52 |
+
translation_output = gr.Textbox(label="Texto traducido")
|
53 |
+
translate_button = gr.Button("Traducir Texto")
|
54 |
+
translate_button.click(translate_text, inputs=[transcript_output, language_selector], outputs=translation_output)
|
55 |
+
|
56 |
+
# Lanzar la interfaz de Gradio
|
57 |
+
demo.launch()
|