@@ -132,7 +132,9 @@ depth = model.infer_image(raw_img) # HxW raw depth map in numpy
132132const diffusers_default = ( model : ModelData ) => [
133133 `from diffusers import DiffusionPipeline
134134
135- pipeline = DiffusionPipeline.from_pretrained("${ model . id } ")` ,
135+ pipeline = DiffusionPipeline.from_pretrained("${ model . id } ")
136+ prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
137+ image = pipeline(prompt).images[0]` ,
136138] ;
137139
138140const diffusers_controlnet = ( model : ModelData ) => [
@@ -148,7 +150,9 @@ const diffusers_lora = (model: ModelData) => [
148150 `from diffusers import DiffusionPipeline
149151
150152pipeline = DiffusionPipeline.from_pretrained("${ get_base_diffusers_model ( model ) } ")
151- pipeline.load_lora_weights("${ model . id } ")` ,
153+ pipeline.load_lora_weights("${ model . id } ")
154+ prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
155+ image = pipeline(prompt).images[0]` ,
152156] ;
153157
154158const diffusers_textual_inversion = ( model : ModelData ) => [
@@ -746,8 +750,8 @@ export const transformers = (model: ModelData): string[] => {
746750 info . processor === "AutoTokenizer"
747751 ? "tokenizer"
748752 : info . processor === "AutoFeatureExtractor"
749- ? "extractor"
750- : "processor" ;
753+ ? "extractor"
754+ : "processor" ;
751755 autoSnippet = [
752756 "# Load model directly" ,
753757 `from transformers import ${ info . processor } , ${ info . auto_model } ` ,
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