optimum-neuron/v0.4.3/en/_app/immutable/nodes/23.05573e75.js

import{s as bt,a as _t,n as Tt,o as wt}from"../chunks/scheduler.56725da7.js";import{S as Jt,i as Ut,e as r,s as o,c as s,h as vt,a as i,d as n,b as a,f as J,g as m,j as h,k as M,l as le,m as l,n as p,t as u,o as c,p as d}from"../chunks/index.18a26576.js";import{C as Nt}from"../chunks/CopyLLMTxtMenu.3134fcef.js";import{D as me}from"../chunks/Docstring.69b6e7bf.js";import{C as oe}from"../chunks/CodeBlock.b87ef962.js";import{H as ae}from"../chunks/MermaidChart.svelte_svelte_type_style_lang.868449a1.js";function jt(et){let f,ce,pe,de,U,Me,v,he,N,tt="Flux is a series of text-to-image generation models based on diffusion transformers.",fe,w,nt="<p>We recommend using a <code>inf2.24xlarge</code> instance with tensor parallel size 8 for the model compilation and inference.</p>",ye,j,ge,x,lt="<li>Option 1: CLI</li>",_e,$,be,C,ot="<li>Option 2: Python API</li>",Te,Z,we,I,Je,X,at="<li>The guidance-distilled variant takes about 50 sampling steps for good-quality generation.</li>",Ue,G,ve,y,rt,Ne,k,je,B,it="<li>max_sequence_length cannot be more than 256.</li> <li>guidance_scale needs to be 0.</li> <li>As this is a timestep-distilled model, it benefits from fewer sampling steps.</li>",xe,F,$e,V,Ce,g,st,Ze,W,Ie,S,mt="The Flux pipeline for text-to-image generation.",Xe,_,z,De,re,R,Ge,E,ke,L,pt="The Flux pipeline for image inpainting.",Be,b,Q,Ke,ie,Y,Fe,H,ut="With <code>NeuronFluxInpaintPipeline</code>, pass the original image and a mask of what you want to replace in the original image. Then replace the masked area with content described in a prompt.",Ve,P,We,A,Se,q,ct="The Flux pipeline for image editing.",ze,T,D,Oe,se,K,Re,O,dt="With <code>NeuronFluxKontextPipeline</code>, pass the original image and a prompt describing what you want to change about the original image.",Ee,ee,Le,te,Mt='<thead><tr><th align="center">Image</th> <th align="center">Prompt</th> <th align="center">Output</th></tr></thead> <tbody><tr><td align="center"><img src="https://huggingface.co/datasets/Jlonge4/document_images/resolve/main/flux_optimum.png" alt="red_cushions" width="250"/></td> <td align="center"><strong><em>Change the cushions in the chair from red to green</em></strong></td> <td align="center"><img src="https://huggingface.co/datasets/Jlonge4/document_images/resolve/main/flux_optimum_edit.png" alt="green_cushions" width="250"/></td></tr></tbody>',Qe,ne,ht='Are there any other diffusion features that you want us to support in 🤗<code>Optimum-neuron</code>? Please file an issue to <a href="https://github.com/huggingface/optimum-neuron" rel="nofollow"><code>Optimum-neuron</code> Github repo</a> or discuss with us on <a href="https://discuss.huggingface.co/c/optimum/" rel="nofollow">HuggingFace’s community forum</a>, cheers 🤗 !',Ye,ue,He;return U=new Nt({props:{containerStyle:"float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"}}),v=new ae({props:{title:"Flux",local:"flux",headingTag:"h1"}}),j=new ae({props:{title:"Export to Neuron",local:"export-to-neuron",headingTag:"h3"}}),$=new oe({props:{code:"b3B0aW11bS1jbGklMjBleHBvcnQlMjBuZXVyb24lMjAtLW1vZGVsJTIwYmxhY2stZm9yZXN0LWxhYnMlMkZGTFVYLjEtZGV2JTIwLS10ZW5zb3JfcGFyYWxsZWxfc2l6ZSUyMDglMjAtLWJhdGNoX3NpemUlMjAxJTIwLS1oZWlnaHQlMjAxMDI0JTIwLS13aWR0aCUyMDEwMjQlMjAtLW51bV9pbWFnZXNfcGVyX3Byb21wdCUyMDElMjAtLXRvcmNoX2R0eXBlJTIwYmZsb2F0MTYlMjBmbHV4X2Rldl9uZXVyb24lMkY=",highlighted:'optimum-cli <span class="hljs-built_in">export</span> neuron --model black-forest-labs/FLUX.1-dev --tensor_parallel_size 8 --batch_size 1 --height 1024 --width 1024 --num_images_per_prompt 1 --torch_dtype bfloat16 flux_dev_neuron/',wrap:!1}}),Z=new oe({props:{code:"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",highlighted:`<span class="hljs-keyword">from</span> optimum.neuron <span class="hljs-keyword">import</span> NeuronFluxPipeline

<span class="hljs-keyword">if</span> __name__ == <span class="hljs-string">&quot;__main__&quot;</span>:
    compiler_args = {<span class="hljs-string">&quot;auto_cast&quot;</span>: <span class="hljs-string">&quot;none&quot;</span>}
    input_shapes = {<span class="hljs-string">&quot;batch_size&quot;</span>: <span class="hljs-number">1</span>, <span class="hljs-string">&quot;height&quot;</span>: <span class="hljs-number">1024</span>, <span class="hljs-string">&quot;width&quot;</span>: <span class="hljs-number">1024</span>}

    pipe = NeuronFluxPipeline.from_pretrained(
        <span class="hljs-string">&quot;black-forest-labs/FLUX.1-dev&quot;</span>,
        torch_dtype=torch.bfloat16,
        export=<span class="hljs-literal">True</span>,
        tensor_parallel_size=<span class="hljs-number">8</span>,
        **compiler_args,
        **input_shapes
    )

    <span class="hljs-comment"># Save locally</span>
    pipe.save_pretrained(<span class="hljs-string">&quot;flux_dev_neuron_1024_tp8/&quot;</span>)

    <span class="hljs-comment"># Upload to the HuggingFace Hub</span>
    pipe.push_to_hub(
        <span class="hljs-string">&quot;flux_dev_neuron_1024_tp8/&quot;</span>, repository_id=<span class="hljs-string">&quot;Jingya/FLUX.1-dev-neuronx-1024x1024-tp8&quot;</span>  <span class="hljs-comment"># Replace with your HF Hub repo id</span>
    )`,wrap:!1}}),I=new ae({props:{title:"Guidance-distilled",local:"guidance-distilled",headingTag:"h2"}}),G=new oe({props:{code:"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",highlighted:`<span class="hljs-keyword">from</span> optimum.neuron <span class="hljs-keyword">import</span> NeuronFluxPipeline

pipe = NeuronFluxPipeline.from_pretrained(<span class="hljs-string">&quot;flux_dev_neuron_1024_tp8/&quot;</span>)
prompt = <span class="hljs-string">&quot;A cat holding a sign that says hello world&quot;</span>
out = pipe(
    prompt,
    guidance_scale=<span class="hljs-number">3.5</span>,
    num_inference_steps=<span class="hljs-number">50</span>,
    generator=torch.Generator(<span class="hljs-string">&quot;cpu&quot;</span>).manual_seed(<span class="hljs-number">0</span>)
).images[<span class="hljs-number">0</span>]
out.save(<span class="hljs-string">&quot;flux_optimum.png&quot;</span>)`,wrap:!1}}),k=new ae({props:{title:"Timestep-distilled",local:"timestep-distilled",headingTag:"h2"}}),F=new oe({props:{code:"b3B0aW11bS1jbGklMjBleHBvcnQlMjBuZXVyb24lMjAtLW1vZGVsJTIwYmxhY2stZm9yZXN0LWxhYnMlMkZGTFVYLjEtc2NobmVsbCUyMC0tdGVuc29yX3BhcmFsbGVsX3NpemUlMjA4JTIwLS1iYXRjaF9zaXplJTIwMSUyMC0taGVpZ2h0JTIwMTAyNCUyMC0td2lkdGglMjAxMDI0JTIwLS1udW1faW1hZ2VzX3Blcl9wcm9tcHQlMjAxJTIwLS1zZXF1ZW5jZV9sZW5ndGglMjAyNTYlMjAtLXRvcmNoX2R0eXBlJTIwYmZsb2F0MTYlMjBmbHV4X3NjaG5lbGxfbmV1cm9uXzEwMjRfdHA4JTJG",highlighted:'optimum-cli <span class="hljs-built_in">export</span> neuron --model black-forest-labs/FLUX.1-schnell --tensor_parallel_size 8 --batch_size 1 --height 1024 --width 1024 --num_images_per_prompt 1 --sequence_length 256 --torch_dtype bfloat16 flux_schnell_neuron_1024_tp8/',wrap:!1}}),V=new oe({props:{code:"ZnJvbSUyMG9wdGltdW0ubmV1cm9uJTIwaW1wb3J0JTIwTmV1cm9uRmx1eFBpcGVsaW5lJTBBJTBBcGlwZSUyMCUzRCUyME5ldXJvbkZsdXhQaXBlbGluZS5mcm9tX3ByZXRyYWluZWQoJTIyZmx1eF9zY2huZWxsX25ldXJvbl8xMDI0X3RwOCUyMiklMEFwcm9tcHQlMjAlM0QlMjAlMjJBJTIwY2F0JTIwaG9sZGluZyUyMGElMjBzaWduJTIwdGhhdCUyMHNheXMlMjBoZWxsbyUyMHdvcmxkJTIyJTBBb3V0JTIwJTNEJTIwcGlwZShwcm9tcHQlMkMlMjBtYXhfc2VxdWVuY2VfbGVuZ3RoJTNEMjU2JTJDJTIwbnVtX2luZmVyZW5jZV9zdGVwcyUzRDQpLmltYWdlcyU1QjAlNUQ=",highlighted:`<span class="hljs-keyword">from</span> optimum.neuron <span class="hljs-keyword">import</span> NeuronFluxPipeline

pipe = NeuronFluxPipeline.from_pretrained(<span class="hljs-string">&quot;flux_schnell_neuron_1024_tp8&quot;</span>)
prompt = <span class="hljs-string">&quot;A cat holding a sign that says hello world&quot;</span>
out = pipe(prompt, max_sequence_length=<span class="hljs-number">256</span>, num_inference_steps=<span class="hljs-number">4</span>).images[<span class="hljs-number">0</span>]`,wrap:!1}}),W=new ae({props:{title:"NeuronFluxPipeline",local:"optimum.neuron.NeuronFluxPipeline",headingTag:"h2"}}),z=new me({props:{name:"class optimum.neuron.NeuronFluxPipeline",anchor:"optimum.neuron.NeuronFluxPipeline",parameters:[{name:"config",val:": dict[str, typing.Any]"},{name:"configs",val:": dict[str, 'PretrainedConfig']"},{name:"neuron_configs",val:": dict[str, 'NeuronDefaultConfig']"},{name:"data_parallel_mode",val:": typing.Literal['none', 'unet', 'transformer', 'all']"},{name:"scheduler",val:": diffusers.schedulers.scheduling_utils.SchedulerMixin | None"},{name:"vae_decoder",val:": torch.jit._script.ScriptModule | NeuronModelVaeDecoder"},{name:"text_encoder",val:": torch.jit._script.ScriptModule | NeuronModelTextEncoder | None = None"},{name:"text_encoder_2",val:": torch.jit._script.ScriptModule | NeuronModelTextEncoder | None = None"},{name:"unet",val:": torch.jit._script.ScriptModule | NeuronModelUnet | None = None"},{name:"transformer",val:": torch.jit._script.ScriptModule | NeuronModelTransformer | None = None"},{name:"vae_encoder",val:": torch.jit._script.ScriptModule | NeuronModelVaeEncoder | None = None"},{name:"image_encoder",val:": torch.jit._script.ScriptModule | None = None"},{name:"safety_checker",val:": torch.jit._script.ScriptModule | None = None"},{name:"tokenizer",val:": transformers.models.clip.tokenization_clip.CLIPTokenizer | transformers.models.t5.tokenization_t5.T5Tokenizer | None = None"},{name:"tokenizer_2",val:": transformers.models.clip.tokenization_clip.CLIPTokenizer | transformers.models.t5.tokenization_t5.T5Tokenizer | None = None"},{name:"feature_extractor",val:": transformers.models.clip.feature_extraction_clip.CLIPFeatureExtractor | None = None"},{name:"controlnet",val:": torch.jit._script.ScriptModule | list[torch.jit._script.ScriptModule]| NeuronControlNetModel | NeuronMultiControlNetModel | None = None"},{name:"requires_aesthetics_score",val:": bool = False"},{name:"force_zeros_for_empty_prompt",val:": bool = True"},{name:"add_watermarker",val:": bool | None = None"},{name:"model_save_dir",val:": str | pathlib.Path | tempfile.TemporaryDirectory | None = None"},{name:"model_and_config_save_paths",val:": dict[str, tuple[str, pathlib.Path]] | None = None"}],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.3/optimum/neuron/modeling_diffusion.py#L1620"}}),R=new me({props:{name:"__call__",anchor:"optimum.neuron.NeuronFluxPipeline.__call__",parameters:[{name:"*args",val:""},{name:"**kwargs",val:""}],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.3/optimum/neuron/modeling_diffusion.py#L1094"}}),E=new ae({props:{title:"NeuronFluxInpaintPipeline",local:"optimum.neuron.NeuronFluxInpaintPipeline",headingTag:"h2"}}),Q=new me({props:{name:"class optimum.neuron.NeuronFluxInpaintPipeline",anchor:"optimum.neuron.NeuronFluxInpaintPipeline",parameters:[{name:"config",val:": dict[str, typing.Any]"},{name:"configs",val:": dict[str, 'PretrainedConfig']"},{name:"neuron_configs",val:": dict[str, 'NeuronDefaultConfig']"},{name:"data_parallel_mode",val:": typing.Literal['none', 'unet', 'transformer', 'all']"},{name:"scheduler",val:": diffusers.schedulers.scheduling_utils.SchedulerMixin | None"},{name:"vae_decoder",val:": torch.jit._script.ScriptModule | NeuronModelVaeDecoder"},{name:"text_encoder",val:": torch.jit._script.ScriptModule | NeuronModelTextEncoder | None = None"},{name:"text_encoder_2",val:": torch.jit._script.ScriptModule | NeuronModelTextEncoder | None = None"},{name:"unet",val:": torch.jit._script.ScriptModule | NeuronModelUnet | None = None"},{name:"transformer",val:": torch.jit._script.ScriptModule | NeuronModelTransformer | None = None"},{name:"vae_encoder",val:": torch.jit._script.ScriptModule | NeuronModelVaeEncoder | None = None"},{name:"image_encoder",val:": torch.jit._script.ScriptModule | None = None"},{name:"safety_checker",val:": torch.jit._script.ScriptModule | None = None"},{name:"tokenizer",val:": transformers.models.clip.tokenization_clip.CLIPTokenizer | transformers.models.t5.tokenization_t5.T5Tokenizer | None = None"},{name:"tokenizer_2",val:": transformers.models.clip.tokenization_clip.CLIPTokenizer | transformers.models.t5.tokenization_t5.T5Tokenizer | None = None"},{name:"feature_extractor",val:": transformers.models.clip.feature_extraction_clip.CLIPFeatureExtractor | None = None"},{name:"controlnet",val:": torch.jit._script.ScriptModule | list[torch.jit._script.ScriptModule]| NeuronControlNetModel | NeuronMultiControlNetModel | None = None"},{name:"requires_aesthetics_score",val:": bool = False"},{name:"force_zeros_for_empty_prompt",val:": bool = True"},{name:"add_watermarker",val:": bool | None = None"},{name:"model_save_dir",val:": str | pathlib.Path | tempfile.TemporaryDirectory | None = None"},{name:"model_and_config_save_paths",val:": dict[str, tuple[str, pathlib.Path]] | None = None"}],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.3/optimum/neuron/modeling_diffusion.py#L1630"}}),Y=new me({props:{name:"__call__",anchor:"optimum.neuron.NeuronFluxInpaintPipeline.__call__",parameters:[{name:"*args",val:""},{name:"**kwargs",val:""}],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.3/optimum/neuron/modeling_diffusion.py#L1094"}}),P=new oe({props:{code:"ZnJvbSUyMGRpZmZ1c2Vycy51dGlscyUyMGltcG9ydCUyMGxvYWRfaW1hZ2UlMEFmcm9tJTIwb3B0aW11bS5uZXVyb24lMjBpbXBvcnQlMjBOZXVyb25GbHV4SW5wYWludFBpcGVsaW5lJTBBJTBBcGlwZSUyMCUzRCUyME5ldXJvbkZsdXhJbnBhaW50UGlwZWxpbmUuZnJvbV9wcmV0cmFpbmVkKCUyMkppbmd5YSUyRkZsdXguMS1TY2huZWxsLTEwMjR4MTAyNC1uZXVyb254LXRwOCUyMiklMEFwcm9tcHQlMjAlM0QlMjAlMjJGYWNlJTIwb2YlMjBhJTIweWVsbG93JTIwY2F0JTJDJTIwaGlnaCUyMHJlc29sdXRpb24lMkMlMjBzaXR0aW5nJTIwb24lMjBhJTIwcGFyayUyMGJlbmNoJTIyJTBBaW1nX3VybCUyMCUzRCUyMCUyMmh0dHBzJTNBJTJGJTJGcmF3LmdpdGh1YnVzZXJjb250ZW50LmNvbSUyRkNvbXBWaXMlMkZsYXRlbnQtZGlmZnVzaW9uJTJGbWFpbiUyRmRhdGElMkZpbnBhaW50aW5nX2V4YW1wbGVzJTJGb3ZlcnR1cmUtY3JlYXRpb25zLTVzSTZmUWdZSXVvLnBuZyUyMiUwQW1hc2tfdXJsJTIwJTNEJTIwJTIyaHR0cHMlM0ElMkYlMkZyYXcuZ2l0aHVidXNlcmNvbnRlbnQuY29tJTJGQ29tcFZpcyUyRmxhdGVudC1kaWZmdXNpb24lMkZtYWluJTJGZGF0YSUyRmlucGFpbnRpbmdfZXhhbXBsZXMlMkZvdmVydHVyZS1jcmVhdGlvbnMtNXNJNmZRZ1lJdW9fbWFzay5wbmclMjIlMEFzb3VyY2UlMjAlM0QlMjBsb2FkX2ltYWdlKGltZ191cmwpJTBBbWFzayUyMCUzRCUyMGxvYWRfaW1hZ2UobWFza191cmwpJTBBaW1hZ2VzJTIwJTNEJTIwcGlwZShwcm9tcHQlM0Rwcm9tcHQlMkMlMjBpbWFnZSUzRHNvdXJjZSUyQyUyMG1hc2tfaW1hZ2UlM0RtYXNrJTJDJTIwbWF4X3NlcXVlbmNlX2xlbmd0aCUzRDI1Nik=",highlighted:`<span class="hljs-keyword">from</span> diffusers.utils <span class="hljs-keyword">import</span> load_image
<span class="hljs-keyword">from</span> optimum.neuron <span class="hljs-keyword">import</span> NeuronFluxInpaintPipeline

pipe = NeuronFluxInpaintPipeline.from_pretrained(<span class="hljs-string">&quot;Jingya/Flux.1-Schnell-1024x1024-neuronx-tp8&quot;</span>)
prompt = <span class="hljs-string">&quot;Face of a yellow cat, high resolution, sitting on a park bench&quot;</span>
img_url = <span class="hljs-string">&quot;https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png&quot;</span>
mask_url = <span class="hljs-string">&quot;https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo_mask.png&quot;</span>
source = load_image(img_url)
mask = load_image(mask_url)
images = pipe(prompt=prompt, image=source, mask_image=mask, max_sequence_length=<span class="hljs-number">256</span>)`,wrap:!1}}),A=new ae({props:{title:"NeuronFluxKontextPipeline",local:"optimum.neuron.NeuronFluxKontextPipeline",headingTag:"h2"}}),D=new me({props:{name:"class optimum.neuron.NeuronFluxKontextPipeline",anchor:"optimum.neuron.NeuronFluxKontextPipeline",parameters:[{name:"config",val:": dict[str, typing.Any]"},{name:"configs",val:": dict[str, 'PretrainedConfig']"},{name:"neuron_configs",val:": dict[str, 'NeuronDefaultConfig']"},{name:"data_parallel_mode",val:": typing.Literal['none', 'unet', 'transformer', 'all']"},{name:"scheduler",val:": diffusers.schedulers.scheduling_utils.SchedulerMixin | None"},{name:"vae_decoder",val:": torch.jit._script.ScriptModule | NeuronModelVaeDecoder"},{name:"text_encoder",val:": torch.jit._script.ScriptModule | NeuronModelTextEncoder | None = None"},{name:"text_encoder_2",val:": torch.jit._script.ScriptModule | NeuronModelTextEncoder | None = None"},{name:"unet",val:": torch.jit._script.ScriptModule | NeuronModelUnet | None = None"},{name:"transformer",val:": torch.jit._script.ScriptModule | NeuronModelTransformer | None = None"},{name:"vae_encoder",val:": torch.jit._script.ScriptModule | NeuronModelVaeEncoder | None = None"},{name:"image_encoder",val:": torch.jit._script.ScriptModule | None = None"},{name:"safety_checker",val:": torch.jit._script.ScriptModule | None = None"},{name:"tokenizer",val:": transformers.models.clip.tokenization_clip.CLIPTokenizer | transformers.models.t5.tokenization_t5.T5Tokenizer | None = None"},{name:"tokenizer_2",val:": transformers.models.clip.tokenization_clip.CLIPTokenizer | transformers.models.t5.tokenization_t5.T5Tokenizer | None = None"},{name:"feature_extractor",val:": transformers.models.clip.feature_extraction_clip.CLIPFeatureExtractor | None = None"},{name:"controlnet",val:": torch.jit._script.ScriptModule | list[torch.jit._script.ScriptModule]| NeuronControlNetModel | NeuronMultiControlNetModel | None = None"},{name:"requires_aesthetics_score",val:": bool = False"},{name:"force_zeros_for_empty_prompt",val:": bool = True"},{name:"add_watermarker",val:": bool | None = None"},{name:"model_save_dir",val:": str | pathlib.Path | tempfile.TemporaryDirectory | None = None"},{name:"model_and_config_save_paths",val:": dict[str, tuple[str, pathlib.Path]] | None = None"}],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.3/optimum/neuron/modeling_diffusion.py#L1625"}}),K=new me({props:{name:"__call__",anchor:"optimum.neuron.NeuronFluxKontextPipeline.__call__",parameters:[{name:"*args",val:""},{name:"**kwargs",val:""}],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.3/optimum/neuron/modeling_diffusion.py#L1094"}}),ee=new oe({props:{code:"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",highlighted:`<span class="hljs-keyword">from</span> diffusers.utils <span class="hljs-keyword">import</span> load_image
<span class="hljs-keyword">from</span> optimum.neuron <span class="hljs-keyword">import</span> NeuronFluxKontextPipeline

pipe = NeuronFluxKontextPipeline.from_pretrained(<span class="hljs-string">&quot;Jlonge4/FLUX.1-kontext-neuronx-1024x1024-tp8&quot;</span>)
prompt = <span class="hljs-string">&quot;Change the cushions in the chair from red to green&quot;</span>
img_url = <span class="hljs-string">&quot;https://huggingface.co/datasets/Jlonge4/document_images/resolve/main/flux_optimum.png&quot;</span>
source = load_image(img_url)
images = pipe(prompt=prompt, image=source, guidance_scale=<span 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gt=J(se);m(K.$$.fragment,gt),gt.forEach(n),qe.forEach(n),Re=a(e),O=i(e,"P",{"data-svelte-h":!0}),h(O)!=="svelte-209r0y"&&(O.innerHTML=dt),Ee=a(e),m(ee.$$.fragment,e),Le=a(e),te=i(e,"TABLE",{"data-svelte-h":!0}),h(te)!=="svelte-3kvp36"&&(te.innerHTML=Mt),Qe=a(e),ne=i(e,"P",{"data-svelte-h":!0}),h(ne)!=="svelte-1wos5lv"&&(ne.innerHTML=ht),Ye=a(e),ue=i(e,"P",{}),J(ue).forEach(n),this.h()},h(){M(f,"name","hf:doc:metadata"),M(f,"content",xt),M(w,"class","tip"),_t(y.src,rt="https://huggingface.co/datasets/Jingya/document_images/resolve/main/optimum/neuron/flux_optimum.png")||M(y,"src",rt),M(y,"width","256"),M(y,"height","256"),M(y,"alt","Flux dev generated image."),_t(g.src,st="https://huggingface.co/datasets/Jingya/document_images/resolve/main/optimum/neuron/flux_schnell_optimum.png")||M(g,"src",st),M(g,"width","256"),M(g,"height","256"),M(g,"alt","Flux schnell generated image."),M(re,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 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