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If a launch failed, check the model Logs tab first. You can also send a report from the dashboard sidebar (Feedback / incident form). For email, see contact support and include model id, timestamp, and error message. Below are common error names, messages, causes, and fixes.

Authentication and permissions

InvalidAPIKeyError

Message: Invalid or restricted API key.
Cause: API key is missing, expired, revoked, or restricted.
Fix: Confirm the key, check status in the dashboard, generate a new key if needed, and send Authorization: Bearer <key>.

PermissionError

Message: Permission error: <details>
Cause: Account or key lacks permission for the resource.
Fix: Verify role/permissions and ensure the key belongs to a user with access.

InvalidHFTokenError

Message: Invalid Hugging Face token, please check the token and try again.
Cause: HF token is invalid or expired.
Fix: Re-enter a valid HF token in model settings and redeploy.

Billing, quotas, and spend control

InsufficientCreditsError

Message: Insufficient credits. Please add more credits to your account.
Cause: Account balance is too low.
Fix: Add credits on the Billing page or reduce deployment cost. See Billing.

MaxTokensError

Message: The maximum allowed number of tokens for this completion has been reached.
Cause: Request exceeded token limits.
Fix: Reduce prompt size, lower max_tokens, or increase context in deployment settings.

Model lifecycle and deployment

ModelLoadError

Message: Model load error, please see model logs for more details
Cause: Inference server failed to load model files.
Fix: Inspect logs. Verify file layout, VRAM, quantization, and retry deployment.

ModelNotFoundError

Message: Model <id> not found
Cause: Wrong or deleted model ID.
Fix: Confirm model ID from the dashboard.

ModelNotReadyError

Message: Model <id> not ready
Cause: Model is still being provisioned, building, or an instance is still loading.
Fix: Retry after a moment. If the model is Building, wait for deployment to finish. If errors persist, check logs for stalled provisioning.

ModelBuildingError

Message: It is not possible to query a model that is building.
Cause: Model is in the build phase.
Fix: Wait and monitor build logs.

DeploymentFailedError

Message: It is not possible to query a failed model. or Deployment failed, please check the deployment logs for more details.
Cause: Deployment failed.
Fix: Inspect deployment logs. Contact support with logs and model ID if needed.

FailedStressTestError

Message: Failed to stress test the model.
Cause: Model did not pass stability/throughput tests.
Fix: Check logs for memory/timeout spikes; try smaller batch size or different hardware.

InvalidQuantizationError

Message: Invalid quantization.
Cause: Unsupported or corrupted quantization.
Fix: Redeploy with a supported precision/quantization.

Input, preprocessing, and templates

PreprocessingError

Message: There was an error with the preprocessing of the inputs.
Cause: Preprocessors failed on audio, video, or image inputs.
Fix: Validate and re-encode inputs; test with text-only input to isolate the issue.

URLContentLoadError

Message: Failed to the content on url in the model's inputs.
Cause: URL unreachable or unsupported content type.
Fix: Verify the URL is publicly accessible or upload content directly.

InvalidParameterError

Message: Invalid parameter: <details>
Cause: Missing or malformed request parameter.
Fix: Validate request schema against the API reference and Supported tasks.

InvalidMessageError

Message: Invalid message: <details>
Cause: Message content violates chat endpoint schema.
Fix: Confirm conversation/message structure matches the expected JSON schema.

InvalidConversationError

Message: The structure of the conversation is invalid.
Cause: Conversation object has missing fields or invalid order.
Fix: Reformat the conversation payload.

ChatTemplateError

Message: There was an error with the chat template when applying it to the inputs.
Cause: Chat template placeholders do not match inputs.
Fix: Update the chat template in model settings or adjust input keys.

NoChatTemplateError

Message: No chat template found for this model
Cause: Model expects a chat_template for chat endpoints.
Fix: Provide chat_template in the request or configure a default in model settings.

Endpoints and capabilities

EndpointNotSupportedError

Message: The endpoint <endpoint> is not supported for this model.
Cause: The model does not expose that endpoint.
Fix: Use a supported endpoint from Supported tasks or redeploy with the required pipeline.

PrecisionRequiredError

Message: No default precision found for this model.
Cause: Model requires explicit precision/quantization.
Fix: Set precision in deployment settings and redeploy.

Hugging Face and repository

InvalidHFModelError

Message: Invalid Hugging Face model name
Cause: Incorrect or missing HF repo name.
Fix: Verify repo name and access.

RevisionNotFoundError

Message: Provided revision for this model was not found
Cause: Branch/tag/commit does not exist.
Fix: Use a valid revision or omit to use default.

GatedRepoError

Message: This model is gated and requires a valid token
Cause: HF repo access is restricted.
Fix: Provide a valid HF token with repo permissions.

DisabledRepoError

Message: This model on Hugging Face is disabled
Cause: HF repo disabled by owner or platform.
Fix: Re-enable repo or use a different model.

HfHubHTTPError / HuggingFaceError

Cause: Hugging Face Hub returned an error while fetching assets.
Fix: Check HF status, token validity, and repo configuration in logs.

Runtime and internal

InternalError

Message: Internal error: <details>
Cause: Unexpected server-side failure.
Fix: Check logs and report to support with timestamps.

APIError

Cause: Generic API failure.
Fix: Inspect request/response details and server logs.

RopeScalingError

Message: The backend failed to apply RoPE scaling to the model.
Cause: RoPE scaling failed for large context or incompatible weights.
Fix: Reduce context size or redeploy with different config.

When to contact support

If logs and the fixes above do not resolve the issue, contact support with:
  • Model ID and deployment ID
  • Timestamp of the failing request
  • Error name and message from the UI or API response
  • Steps to reproduce
Check Status and uptime for platform-wide incidents before opening a ticket.