Spaces:
Sleeping
Sleeping
Update app.py
Browse files
app.py
CHANGED
@@ -7,7 +7,7 @@ from PIL import Image
|
|
7 |
# Load models
|
8 |
def load_models():
|
9 |
image_to_text = pipeline("image-to-text", model="Salesforce/blip-image-captioning-base")
|
10 |
-
storyteller = pipeline("text2text-generation", model="google/flan-t5-small", max_length=
|
11 |
return image_to_text, storyteller
|
12 |
|
13 |
# Process image to text
|
@@ -17,7 +17,7 @@ def generate_caption(image, image_to_text):
|
|
17 |
|
18 |
# Generate a narrative story using an optimized Flan-T5 prompt
|
19 |
def generate_story(text, storyteller):
|
20 |
-
prompt = f"Write a creative and engaging short story based on
|
21 |
story = storyteller(prompt)
|
22 |
return story[0]["generated_text"] if story else "No story generated."
|
23 |
|
|
|
7 |
# Load models
|
8 |
def load_models():
|
9 |
image_to_text = pipeline("image-to-text", model="Salesforce/blip-image-captioning-base")
|
10 |
+
storyteller = pipeline("text2text-generation", model="google/flan-t5-small", max_length=100) # Max tokens set to 100
|
11 |
return image_to_text, storyteller
|
12 |
|
13 |
# Process image to text
|
|
|
17 |
|
18 |
# Generate a narrative story using an optimized Flan-T5 prompt
|
19 |
def generate_story(text, storyteller):
|
20 |
+
prompt = f"Write a 75-word creative and engaging short story based on the following description: {text}."
|
21 |
story = storyteller(prompt)
|
22 |
return story[0]["generated_text"] if story else "No story generated."
|
23 |
|