GetModelsResponseSchema
message object[]required
List of owned or fine-tuned model objects.
ID of the base model this owned model was derived from.
Human-readable creation timestamp.
Unique numeric identifier for this owned model.
Name of the owned model (user-assigned or auto-generated).
Organization ID that owns this model.
Current lifecycle state of the model (e.g., "dormant", "deploying", "deployed").
Model origin type. Values: "fine_tuned", "third_party".
ID of the user who owns this model.
base_model_data object
Full metadata of the base model.
Whether this model can be used for fine-tuning jobs.
Whether this model can be deployed for inference.
Total batch size used during fine-tuning.
Number of gradient accumulation steps for fine-tuning.
Learning rate for fine-tuning.
Per-device micro-batch size for fine-tuning.
List of active deployment records associated with this model.
Human-readable name for the model shown in the UI.
Hugging Face repository identifier for this model.
Unique numeric identifier for the base model.
Canonical model identifier used in API requests.
Category of model. Common values: "language_model", "image_model".
Maximum context length (in tokens) supported by this model.
List of region identifiers where this model is available for deployment.
Estimated training time (in seconds) per log step, used for duration projections.
Y-intercept of the training time regression curve, used for fine-tuning duration estimates.
Maximum allowed size (in bytes) for a Hugging Face LoRA adapter when fine-tuning this model.
Cost in USD per million input tokens for inference.
Whether this model was imported by the user (third-party) rather than provided natively by Hyperstack.
Cost in USD per million output tokens for inference.
Estimated training cost per log step, used for fine-tuning cost projections.
Input modalities the model accepts, such as text and image. A model that lists image supports image-to-text input.
Output modalities the model produces, such as text.
Unix epoch timestamp of model creation.
Detailed current state label, if available.
ID of the training dataset used to fine-tune this model, if applicable.
Active deployment records for this model.
Metadata about the model download task, if this is a third-party import.
Total elapsed minutes for the fine-tuning job, if applicable.
Human-readable timestamp of the last deployment.
Unix epoch timestamp of the last deployment.
Human-readable timestamp of the last inference request.
Unix epoch timestamp of the last inference request.
Fine-tuning configuration parameters used to train this model.
Evaluation results for this model, if available.
Current status of each evaluation benchmark (e.g., mix_eval, needlehaystack).
ID of the parent model if this model was fine-tuned from another owned model.
Whether this model is self-hosted by the user.
Third-party import metadata (provider, repo, status, etc.), if applicable.
Elapsed training time in minutes for the fine-tuning job.
Human-readable timestamp when training completed.
Unix epoch timestamp when training completed.
Human-readable timestamp of the most recent update.
Indicates the result of the operation. Typically "success".
{
"message": [
{
"base_model_id": 0,
"created_at": "string",
"model_id": 0,
"model_name": "string",
"organization": 0,
"state": "string",
"type": "string",
"user_id": 0,
"base_model_data": {
"available_for_finetuning": true,
"available_for_inference": true,
"default_batch_size": "total",
"default_gradient_accumulation_steps": "number",
"default_lr": "learning",
"default_micro_batch_size": "per-device",
"deployment_records": [
null
],
"display_name": "string",
"hf_repo": "string",
"model_id": 0,
"model_name": "string",
"model_type": "string",
"supported_context_len": 0,
"supported_locations": [
"string"
],
"training_time_per_log": 0,
"training_time_y_intercept": 0,
"allowed_hf_lora_adapter_size": 0,
"input_token_cost_per_m": 0,
"is_third_party": true,
"output_token_cost_per_m": 0,
"training_cost_per_log": 0
},
"created_at_unix": 0,
"current_state": "string",
"dataset_id": 0,
"deployment_records": [
{}
],
"download_task_metadata": {},
"job_elapsed_minutes": 0,
"last_deployed_on": "string",
"last_deployed_on_unix": 0,
"last_used": "string",
"last_used_unix": 0,
"model_config": {},
"model_evaluation": {},
"model_evaluation_state": {},
"parent_id": 0,
"self_hosted": true,
"third_party_model": {},
"training_elapsed_minutes": 0,
"training_ended_at": "string",
"training_ended_at_unix": 0,
"updated_at": "string"
}
],
"status": "success"
}