xtekky/gpt4free · error · ModelNotFoundError

Model is not supported: {model} in: {cls.__name__}

Error message

Model is not supported: {model} in: {cls.__name__}

What it means

Raised by HuggingFaceMedia when the model-to-provider mapping fetched from the HuggingFace router (filtered/merged for replicate, together, hf-inference) ends up empty. ModelNotFoundError means the router API knows no serving provider for the requested model id, so there is nothing to dispatch to.

Source

Thrown at g4f/Provider/needs_auth/hf/HuggingFaceMedia.py:163

        if model and ":" in model:
            model, selected_provider = model.split(":", 1)
        elif not model:
            model = cls.get_models()[0]
        prompt = format_media_prompt(messages, prompt)
        provider_mapping = await cls.get_mapping(model, api_key)
        headers = {
            "Accept-Encoding": "gzip, deflate",
            "Content-Type": "application/json",
            "Prefer": "wait",
        }
        new_mapping = {
            "hf-free" if key == "hf-inference" else key: value
            for key, value in provider_mapping.items()
            if key in ["replicate", "together", "hf-inference"]
        }
        provider_mapping = {**new_mapping, **provider_mapping}
        if not provider_mapping:
            raise ModelNotFoundError(
                f"Model is not supported: {model} in: {cls.__name__}"
            )

        async def generate(extra_body: dict, aspect_ratio: str = None):
            last_response = None
            for provider_key, provider in provider_mapping.items():
                if selected_provider is not None and selected_provider != provider_key:
                    continue
                provider_info = ProviderInfo(
                    **{
                        **cls.get_dict(),
                        "label": f"HuggingFace ({provider_key})",
                        "url": f"{cls.url}/{model}",
                    }
                )

                base_url = f"https://router.huggingface.co/{provider_key}"
                task = provider["task"]

View on GitHub (pinned to 973504e177)

Solutions

1. Verify the exact model id at huggingface.co — copy the repo name precisely
2. Pick a model that shows Inference Providers on its model page
3. Update g4f in case the mapping endpoint handling changed
4. List supported models via cls.get_models() and choose from those

Example fix

# before
model = 'black-forest-labs/flux-dev-typo'
# after
model = 'black-forest-labs/FLUX.1-dev'

supported = set(HuggingFaceMedia.get_models())
if model not in supported:
    raise ValueError(f'{model} not served; choose from {sorted(supported)[:5]}...')

from g4f.errors import ModelNotFoundError
try:
    ...
except ModelNotFoundError:
    model = HuggingFaceMedia.get_models()[0]
    ...

When it happens

Trigger: Requesting a HuggingFaceMedia model id that does not exist or has no inference providers registered (get_mapping returns {} or only unsupported providers).

Common situations: Typo'd or outdated model id; model delisted from the inference router; new model not yet registered for inference; region/account restrictions removing all providers.

Related errors

• Model {model} not found
• Model '{_model}' is not supported by LMArena provider.
• Add a "api_key"
• Model is not supported: {model} in: {cls.__name__} task: {ta
• Provider '{item}' not found

AI-assisted analysis of xtekky/gpt4free@973504e177 (2026-08-14). Data as JSON: /api/errors/4f21528c77e0166b. Report an issue: GitHub.