Update multit2i.py

multit2i.py

@@ -60,7 +60,7 @@ def find_model_list(author: str="", tags: list[str]=[], not_tag="", sort: str="l
     limit = limit * 20 if check_status and force_gpu else limit * 5
     models = []
     try:
-        model_infos = api.list_models(author=author, task="text-to-image",
+        model_infos = api.list_models(author=author, #task="text-to-image",
                                        tags=list_uniq(default_tags + tags), cardData=True, sort=sort, limit=limit)
     except Exception as e:
         print(f"Error: Failed to list models.")
@@ -157,8 +157,8 @@ def load_from_model(model_name: str, hf_token: str | Literal[False] | None = Non
         raise ModelNotFoundError(
             f"Could not find model: {model_name}. If it is a private or gated model, please provide your Hugging Face access token (https://huggingface.co/settings/tokens) as the argument for the `hf_token` parameter."
         )
-    #p = response.json().get("pipeline_tag")
-    #if p != "text-to-image": raise ModelNotFoundError(f"This model isn't for text-to-image or unsupported: {model_name}.")
+    p = response.json().get("pipeline_tag")
+    if p != "text-to-image": raise ModelNotFoundError(f"This model isn't for text-to-image or unsupported: {model_name}.")
     headers["X-Wait-For-Model"] = "true"
     client = huggingface_hub.InferenceClient(model=model_name, headers=headers,
                                               token=hf_token, timeout=server_timeout)