monster/Qwen-Image-Layered-MRP-MLX
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Update default prompt

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filipstrand 2024-08-14 11:07:11 +02:00
parent 37a6632259
commit 97028713e1
2 changed files with 3 additions and 3 deletions
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4
README.md
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@ -41,8 +41,8 @@ from flux_1_schnell.models.flux import Flux1Schnell
flux = Flux1Schnell("/Users/filipstrand/.cache/FLUX.1-schnell/")
image = flux.generate_image(
seed=42,
prompt="Luxury food photograph",
seed=3,
prompt="Luxury food photograph of a birthday cake. In the middle it has three candles shaped like letters spelling the word 'MLX'. It has perfect lighting and a cozy background with big bokeh and shallow depth of field. The mood is a sunset balcony in tuscany. The photo is taken from the side of the cake. The scene is complemented by a warm, inviting light that highlights the textures and colors of the ingredients, giving it an appetizing and elegant look.",
config=Config(
num_inference_steps=2,
)

2
src/flux_1_schnell/main.py
View File

@ -5,7 +5,7 @@ flux = Flux1Schnell("/Users/filipstrand/.cache/FLUX.1-schnell/")
image = flux.generate_image(
seed=3,
prompt="Luxury food photograph of an italian Linguine pasta alle vongole dish with lots of clams. It has perfect lighting and a cozy background with big bokeh and shallow depth of field. The mood is a sunset balcony in tuscany. The photo is taken from the side of the plate. The pasta is shiny with sprinkled parmesan cheese and basil leaves on top. The scene is complemented by a warm, inviting light that highlights the textures and colors of the ingredients, giving it an appetizing and elegant look.",
prompt="Luxury food photograph of a birthday cake. In the middle it has three candles shaped like letters spelling the word 'MLX'. It has perfect lighting and a cozy background with big bokeh and shallow depth of field. The mood is a sunset balcony in tuscany. The photo is taken from the side of the cake. The scene is complemented by a warm, inviting light that highlights the textures and colors of the ingredients, giving it an appetizing and elegant look.",
config=Config(
num_inference_steps=2,
)