diff --git a/packages/tasks/src/snippets/curl.ts b/packages/tasks/src/snippets/curl.ts
index 2104a0c29c..c8f39b677e 100644
--- a/packages/tasks/src/snippets/curl.ts
+++ b/packages/tasks/src/snippets/curl.ts
@@ -10,7 +10,7 @@ export const snippetBasic = (model: ModelDataMinimal, accessToken: string): stri
 	-H "Authorization: Bearer ${accessToken || `{API_TOKEN}`}"`;
 
 export const snippetTextGeneration = (model: ModelDataMinimal, accessToken: string): string => {
-	if (model.config?.tokenizer_config?.chat_template) {
+	if (model.tags.includes("conversational")) {
 		// Conversational model detected, so we display a code snippet that features the Messages API
 		return `curl 'https://api-inference.huggingface.co/models/${model.id}/v1/chat/completions' \\
 -H "Authorization: Bearer ${accessToken || `{API_TOKEN}`}" \\
@@ -27,6 +27,32 @@ export const snippetTextGeneration = (model: ModelDataMinimal, accessToken: stri
 	}
 };
 
+export const snippetImageTextToTextGeneration = (model: ModelDataMinimal, accessToken: string): string => {
+	if (model.tags.includes("conversational")) {
+		// Conversational model detected, so we display a code snippet that features the Messages API
+		return `curl 'https://api-inference.huggingface.co/models/${model.id}/v1/chat/completions' \\
+-H "Authorization: Bearer ${accessToken || `{API_TOKEN}`}" \\
+-H 'Content-Type: application/json' \\
+-d '{
+	"model": "${model.id}",
+	"messages": [
+		{
+			"role": "user",
+			"content": [
+				{"type": "image_url", "image_url": {"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"}},
+				{"type": "text", "text": "Describe this image in one sentence."}
+			]
+		}
+	],
+	"max_tokens": 500,
+	"stream": false
+}'
+`;
+	} else {
+		return snippetBasic(model, accessToken);
+	}
+};
+
 export const snippetZeroShotClassification = (model: ModelDataMinimal, accessToken: string): string =>
 	`curl https://api-inference.huggingface.co/models/${model.id} \\
 	-X POST \\
@@ -51,6 +77,7 @@ export const curlSnippets: Partial<Record<PipelineType, (model: ModelDataMinimal
 	summarization: snippetBasic,
 	"feature-extraction": snippetBasic,
 	"text-generation": snippetTextGeneration,
+	"image-text-to-text": snippetImageTextToTextGeneration,
 	"text2text-generation": snippetBasic,
 	"fill-mask": snippetBasic,
 	"sentence-similarity": snippetBasic,
diff --git a/packages/tasks/src/snippets/js.ts b/packages/tasks/src/snippets/js.ts
index 8a621787a7..746a4de377 100644
--- a/packages/tasks/src/snippets/js.ts
+++ b/packages/tasks/src/snippets/js.ts
@@ -24,7 +24,7 @@ query({"inputs": ${getModelInputSnippet(model)}}).then((response) => {
 });`;
 
 export const snippetTextGeneration = (model: ModelDataMinimal, accessToken: string): string => {
-	if (model.config?.tokenizer_config?.chat_template) {
+	if (model.tags.includes("conversational")) {
 		// Conversational model detected, so we display a code snippet that features the Messages API
 		return `import { HfInference } from "@huggingface/inference";
 
@@ -41,6 +41,35 @@ for await (const chunk of inference.chatCompletionStream({
 		return snippetBasic(model, accessToken);
 	}
 };
+
+export const snippetImageTextToTextGeneration = (model: ModelDataMinimal, accessToken: string): string => {
+	if (model.tags.includes("conversational")) {
+		// Conversational model detected, so we display a code snippet that features the Messages API
+		return `import { HfInference } from "@huggingface/inference";
+
+const inference = new HfInference("${accessToken || `{API_TOKEN}`}");
+const imageUrl = "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg";
+
+for await (const chunk of inference.chatCompletionStream({
+	model: "${model.id}",
+	messages: [
+		{
+			"role": "user",
+			"content": [
+				{"type": "image_url", "image_url": {"url": imageUrl}},
+				{"type": "text", "text": "Describe this image in one sentence."},
+			],
+		}
+	],
+	max_tokens: 500,
+})) {
+	process.stdout.write(chunk.choices[0]?.delta?.content || "");
+}`;
+	} else {
+		return snippetBasic(model, accessToken);
+	}
+};
+
 export const snippetZeroShotClassification = (model: ModelDataMinimal, accessToken: string): string =>
 	`async function query(data) {
 	const response = await fetch(
@@ -156,6 +185,7 @@ export const jsSnippets: Partial<Record<PipelineType, (model: ModelDataMinimal,
 	summarization: snippetBasic,
 	"feature-extraction": snippetBasic,
 	"text-generation": snippetTextGeneration,
+	"image-text-to-text": snippetImageTextToTextGeneration,
 	"text2text-generation": snippetBasic,
 	"fill-mask": snippetBasic,
 	"sentence-similarity": snippetBasic,
diff --git a/packages/tasks/src/snippets/python.ts b/packages/tasks/src/snippets/python.ts
index f7c252723d..9ffeed54c2 100644
--- a/packages/tasks/src/snippets/python.ts
+++ b/packages/tasks/src/snippets/python.ts
@@ -5,18 +5,39 @@ import type { ModelDataMinimal } from "./types.js";
 export const snippetConversational = (model: ModelDataMinimal, accessToken: string): string =>
 	`from huggingface_hub import InferenceClient
 
-client = InferenceClient(
-    "${model.id}",
-    token="${accessToken || "{API_TOKEN}"}",
-)
+client = InferenceClient(api_key="${accessToken || "{API_TOKEN}"}")
 
 for message in client.chat_completion(
+	model="${model.id}",
 	messages=[{"role": "user", "content": "What is the capital of France?"}],
 	max_tokens=500,
 	stream=True,
 ):
     print(message.choices[0].delta.content, end="")`;
 
+export const snippetConversationalWithImage = (model: ModelDataMinimal, accessToken: string): string =>
+	`from huggingface_hub import InferenceClient
+
+client = InferenceClient(api_key="${accessToken || "{API_TOKEN}"}")
+
+image_url = "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
+
+for message in client.chat_completion(
+	model="${model.id}",
+	messages=[
+		{
+			"role": "user",
+			"content": [
+				{"type": "image_url", "image_url": {"url": image_url}},
+				{"type": "text", "text": "Describe this image in one sentence."},
+			],
+		}
+	],
+	max_tokens=500,
+	stream=True,
+):
+	print(message.choices[0].delta.content, end="")`;
+
 export const snippetZeroShotClassification = (model: ModelDataMinimal): string =>
 	`def query(payload):
 	response = requests.post(API_URL, headers=headers, json=payload)
@@ -153,9 +174,12 @@ export const pythonSnippets: Partial<Record<PipelineType, (model: ModelDataMinim
 };
 
 export function getPythonInferenceSnippet(model: ModelDataMinimal, accessToken: string): string {
-	if (model.pipeline_tag === "text-generation" && model.config?.tokenizer_config?.chat_template) {
+	if (model.pipeline_tag === "text-generation" && model.tags.includes("conversational")) {
 		// Conversational model detected, so we display a code snippet that features the Messages API
 		return snippetConversational(model, accessToken);
+	} else if (model.pipeline_tag === "image-text-to-text" && model.tags.includes("conversational")) {
+		// Example sending an image to the Message API
+		return snippetConversationalWithImage(model, accessToken);
 	} else {
 		const body =
 			model.pipeline_tag && model.pipeline_tag in pythonSnippets
diff --git a/packages/tasks/src/snippets/types.ts b/packages/tasks/src/snippets/types.ts
index 658c3ebf82..1bdd050ca6 100644
--- a/packages/tasks/src/snippets/types.ts
+++ b/packages/tasks/src/snippets/types.ts
@@ -5,4 +5,7 @@ import type { ModelData } from "../model-data";
  *
  * Add more fields as needed.
  */
-export type ModelDataMinimal = Pick<ModelData, "id" | "pipeline_tag" | "mask_token" | "library_name" | "config">;
+export type ModelDataMinimal = Pick<
+	ModelData,
+	"id" | "pipeline_tag" | "mask_token" | "library_name" | "config" | "tags"
+>;