Add Use this model snippets for top diffusers models (#1642)

Slack:
https://huggingface.slack.com/archives/C04SZ8E2Q6S/p1752664171386139

---------

Co-authored-by: vb <vaibhavs10@gmail.com>

Author: apolinario

packages/tasks/src/model-libraries-snippets.ts

@@ -434,8 +434,63 @@ pipe = DiffusionPipeline.from_pretrained("${get_base_diffusers_model(model)}")
 pipe.load_textual_inversion("${model.id}")`,
 ];
 
+const diffusers_flux_fill = (model: ModelData) => [
+	`import torch
+from diffusers import FluxFillPipeline
+from diffusers.utils import load_image
+
+image = load_image("https://huggingface.co/datasets/diffusers/diffusers-images-docs/resolve/main/cup.png")
+mask = load_image("https://huggingface.co/datasets/diffusers/diffusers-images-docs/resolve/main/cup_mask.png")
+
+pipe = FluxFillPipeline.from_pretrained("${model.id}", torch_dtype=torch.bfloat16).to("cuda")
+image = pipe(
+    prompt="a white paper cup",
+    image=image,
+    mask_image=mask,
+    height=1632,
+    width=1232,
+    guidance_scale=30,
+    num_inference_steps=50,
+    max_sequence_length=512,
+    generator=torch.Generator("cpu").manual_seed(0)
+).images[0]
+image.save(f"flux-fill-dev.png")`,
+];
+
+const diffusers_inpainting = (model: ModelData) => [
+	`import torch
+from diffusers import AutoPipelineForInpainting
+from diffusers.utils import load_image
+
+pipe = AutoPipelineForInpainting.from_pretrained("${model.id}", torch_dtype=torch.float16, variant="fp16").to("cuda")
+
+img_url = "https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png"
+mask_url = "https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo_mask.png"
+
+image = load_image(img_url).resize((1024, 1024))
+mask_image = load_image(mask_url).resize((1024, 1024))
+
+prompt = "a tiger sitting on a park bench"
+generator = torch.Generator(device="cuda").manual_seed(0)
+
+image = pipe(
+  prompt=prompt,
+  image=image,
+  mask_image=mask_image,
+  guidance_scale=8.0,
+  num_inference_steps=20,  # steps between 15 and 30 work well for us
+  strength=0.99,  # make sure to use \`strength\` below 1.0
+  generator=generator,
+).images[0]`,
+];
+
 export const diffusers = (model: ModelData): string[] => {
-	if (model.tags.includes("controlnet")) {
+	if (
+		model.tags.includes("StableDiffusionInpaintPipeline") ||
+		model.tags.includes("StableDiffusionXLInpaintPipeline")
+	) {
+		return diffusers_inpainting(model);
+	} else if (model.tags.includes("controlnet")) {
 		return diffusers_controlnet(model);
 	} else if (model.tags.includes("lora")) {
 		if (model.pipeline_tag === "image-to-image") {
@@ -449,6 +504,8 @@ export const diffusers = (model: ModelData): string[] => {
 		}
 	} else if (model.tags.includes("textual_inversion")) {
 		return diffusers_textual_inversion(model);
+	} else if (model.tags.includes("FluxFillPipeline")) {
+		return diffusers_flux_fill(model);
 	} else if (model.pipeline_tag === "image-to-video") {
 		return diffusers_image_to_video(model);
 	} else if (model.pipeline_tag === "image-to-image") {

packages/tasks/src/model-libraries.ts

@@ -465,12 +465,6 @@ export const MODEL_LIBRARIES_UI_ELEMENTS = {
 		repoUrl: "https://github.com/Tencent/HunyuanDiT",
 		countDownloads: `path:"pytorch_model_ema.pt" OR path:"pytorch_model_distill.pt"`,
 	},
-	"hunyuan3d-2": {
-		prettyLabel: "Hunyuan3D-2",
-		repoName: "Hunyuan3D-2",
-		repoUrl: "https://github.com/Tencent/Hunyuan3D-2",
-		countDownloads: `path_filename:"model_index" OR path_filename:"config"`,
-	},
 	imstoucan: {
 		prettyLabel: "IMS Toucan",
 		repoName: "IMS-Toucan",