Spaces:
Runtime error
Runtime error
Update app.py
Browse files
app.py
CHANGED
|
@@ -1,48 +1,50 @@
|
|
| 1 |
import gradio as gr
|
| 2 |
-
from transformers import MarianMTModel, MarianTokenizer
|
| 3 |
|
| 4 |
def translate(text, target_language):
|
| 5 |
-
|
| 6 |
-
|
| 7 |
-
|
| 8 |
-
|
| 9 |
-
|
| 10 |
-
|
| 11 |
-
|
| 12 |
-
|
| 13 |
-
|
| 14 |
-
|
| 15 |
-
"Dutch": "nl",
|
| 16 |
-
"German": "de",
|
| 17 |
-
"Arabic": "ar",
|
| 18 |
-
"Hebrew": "he",
|
| 19 |
-
"Greek": "el"
|
| 20 |
-
}
|
| 21 |
-
target_language_code = language_codes[target_language]
|
| 22 |
-
model_name = f'helsinki-nlp/opus-mt-en-{target_language_code}'
|
| 23 |
-
tokenizer = MarianTokenizer.from_pretrained(model_name)
|
| 24 |
-
model = MarianMTModel.from_pretrained(model_name)
|
| 25 |
-
inputs = tokenizer(text, return_tensors="pt")
|
| 26 |
-
outputs = model.generate(**inputs)
|
| 27 |
-
translation = tokenizer.decode(outputs[0], skip_special_tokens=True)
|
| 28 |
-
return translation
|
| 29 |
|
| 30 |
language_options = [
|
| 31 |
-
|
| 32 |
-
"Portuguese (Brazilian)", "Portuguese (European)", "Russian", "Chinese",
|
| 33 |
-
"Dutch", "German", "Arabic", "Hebrew", "Greek"
|
| 34 |
]
|
| 35 |
|
| 36 |
-
|
| 37 |
fn=translate,
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 38 |
inputs=[
|
| 39 |
-
gr.inputs.Textbox(lines=5, label="Enter text to translate:"),
|
| 40 |
gr.inputs.Dropdown(choices=language_options, label="Target Language"),
|
| 41 |
],
|
| 42 |
-
outputs=
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 43 |
)
|
| 44 |
|
| 45 |
-
|
|
|
|
| 46 |
|
| 47 |
|
| 48 |
|
|
|
|
| 1 |
import gradio as gr
|
| 2 |
+
from transformers import MarianMTModel, MarianTokenizer, GPT2LMHeadModel, GPT2Tokenizer
|
| 3 |
|
| 4 |
def translate(text, target_language):
|
| 5 |
+
# ... (keep the existing code for translation here)
|
| 6 |
+
|
| 7 |
+
def generate_text(prompt):
|
| 8 |
+
model_name = 'gpt2'
|
| 9 |
+
tokenizer = GPT2Tokenizer.from_pretrained(model_name)
|
| 10 |
+
model = GPT2LMHeadModel.from_pretrained(model_name)
|
| 11 |
+
inputs = tokenizer.encode(prompt, return_tensors='pt')
|
| 12 |
+
outputs = model.generate(inputs, max_length=100, num_return_sequences=1)
|
| 13 |
+
generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
|
| 14 |
+
return generated_text
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 15 |
|
| 16 |
language_options = [
|
| 17 |
+
# ... (keep the existing language options here)
|
|
|
|
|
|
|
| 18 |
]
|
| 19 |
|
| 20 |
+
iface_translation = gr.Interface(
|
| 21 |
fn=translate,
|
| 22 |
+
# ... (keep the existing translation inputs and outputs here)
|
| 23 |
+
)
|
| 24 |
+
|
| 25 |
+
iface_generation = gr.Interface(
|
| 26 |
+
fn=generate_text,
|
| 27 |
+
inputs=gr.inputs.Textbox(lines=5, label="Enter a prompt for text generation:"),
|
| 28 |
+
outputs=gr.outputs.Textbox(label="Generated Text"),
|
| 29 |
+
)
|
| 30 |
+
|
| 31 |
+
# Combine the two interfaces into a single Gradio interface
|
| 32 |
+
iface_combined = gr.Interface(
|
| 33 |
+
[translate, generate_text],
|
| 34 |
inputs=[
|
| 35 |
+
gr.inputs.Textbox(lines=5, label="Enter text to translate / generate:", default="Enter text to translate here."),
|
| 36 |
gr.inputs.Dropdown(choices=language_options, label="Target Language"),
|
| 37 |
],
|
| 38 |
+
outputs=[
|
| 39 |
+
gr.outputs.Textbox(label="Translated Text / Generated Text"),
|
| 40 |
+
],
|
| 41 |
+
title="Translation and Text Generation",
|
| 42 |
+
description="Choose a target language to translate English text or leave it as 'None' for text generation.",
|
| 43 |
+
examples=[["Translate this text to French.", "French (European)"]]
|
| 44 |
)
|
| 45 |
|
| 46 |
+
iface_combined.launch()
|
| 47 |
+
|
| 48 |
|
| 49 |
|
| 50 |
|