diff --git a/packages/tasks/src/model-libraries-snippets.ts b/packages/tasks/src/model-libraries-snippets.ts
index 9782c3bfea..39e973b511 100644
--- a/packages/tasks/src/model-libraries-snippets.ts
+++ b/packages/tasks/src/model-libraries-snippets.ts
@@ -1373,27 +1373,58 @@ export const transformers = (model: ModelData): string[] => {
 	}
 	const remote_code_snippet = model.tags.includes(TAG_CUSTOM_CODE) ? ", trust_remote_code=True" : "";
 
-	let autoSnippet: string;
+	const autoSnippet = [];
 	if (info.processor) {
-		const varName =
+		const processorVarName =
 			info.processor === "AutoTokenizer"
 				? "tokenizer"
 				: info.processor === "AutoFeatureExtractor"
 				  ? "extractor"
 				  : "processor";
-		autoSnippet = [
+		autoSnippet.push(
 			"# Load model directly",
 			`from transformers import ${info.processor}, ${info.auto_model}`,
 			"",
-			`${varName} = ${info.processor}.from_pretrained("${model.id}"` + remote_code_snippet + ")",
-			`model = ${info.auto_model}.from_pretrained("${model.id}"` + remote_code_snippet + ")",
-		].join("\n");
+			`${processorVarName} = ${info.processor}.from_pretrained("${model.id}"` + remote_code_snippet + ")",
+			`model = ${info.auto_model}.from_pretrained("${model.id}"` + remote_code_snippet + ")"
+		);
+		if (model.tags.includes("conversational")) {
+			if (model.tags.includes("image-text-to-text")) {
+				autoSnippet.push(
+					"messages = [",
+					[
+						"    {",
+						'        "role": "user",',
+						'        "content": [',
+						'            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},',
+						'            {"type": "text", "text": "What animal is on the candy?"}',
+						"        ]",
+						"    },",
+					].join("\n"),
+					"]"
+				);
+			} else {
+				autoSnippet.push("messages = [", '    {"role": "user", "content": "Who are you?"},', "]");
+			}
+			autoSnippet.push(
+				"inputs = ${processorVarName}.apply_chat_template(",
+				"	messages,",
+				"	add_generation_prompt=True,",
+				"	tokenize=True,",
+				"	return_dict=True,",
+				'	return_tensors="pt",',
+				").to(model.device)",
+				"",
+				"outputs = model.generate(**inputs, max_new_tokens=40)",
+				'print(${processorVarName}.decode(outputs[0][inputs["input_ids"].shape[-1]:]))'
+			);
+		}
 	} else {
-		autoSnippet = [
+		autoSnippet.push(
 			"# Load model directly",
 			`from transformers import ${info.auto_model}`,
-			`model = ${info.auto_model}.from_pretrained("${model.id}"` + remote_code_snippet + ")",
-		].join("\n");
+			`model = ${info.auto_model}.from_pretrained("${model.id}"` + remote_code_snippet + ', torch_dtype="auto"),'
+		);
 	}
 
 	if (model.pipeline_tag && LIBRARY_TASK_MAPPING.transformers?.includes(model.pipeline_tag)) {
@@ -1437,9 +1468,9 @@ export const transformers = (model: ModelData): string[] => {
 			);
 		}
 
-		return [pipelineSnippet.join("\n"), autoSnippet];
+		return [pipelineSnippet.join("\n"), autoSnippet.join("\n")];
 	}
-	return [autoSnippet];
+	return [autoSnippet.join("\n")];
 };
 
 export const transformersJS = (model: ModelData): string[] => {