Update Model
Path parameters
The Account Id
The Model Id
Request body
Human-readable display name of the model. e.g. "My Model" Must be fewer than 64 characters long.
The description of the model. Must be fewer than 1000 characters long.
The creation time of the model.
- UPLOADING: The model is still being uploaded (upload is asynchronous).
- READY: The model is ready to be used.
- HF_BASE_MODEL: An LLM base model.
- HF_PEFT_ADDON: A parameter-efficent fine-tuned addon.
- HF_TEFT_ADDON: A token-eficient fine-tuned addon.
- FLUMINA_BASE_MODEL: A Flumina base model.
- FLUMINA_ADDON: A Flumina addon.
- DRAFT_ADDON: A draft model used for speculative decoding in a deployment.
- FIRE_AGENT: A FireAgent model.
- LIVE_MERGE: A live-merge model.
- CUSTOM_MODEL: A customized model
- EMBEDDING_MODEL: An Embedding model.
- SNAPSHOT_MODEL: A snapshot model.
The URL to GitHub repository of the model.
The URL to the Hugging Face model.
If true, the model will be publicly readable.
The maximum context length supported by the model.
If set, images can be provided as input to the model.
If set, tools (i.e. functions) can be provided as input to the model, and the model may respond with one or more tool calls.
The name of the the model from which this was imported. This field is empty if the model was not imported.
If the model was created from a fine-tuning job, this is the fine-tuning job name.
The default draft model to use when creating a deployment. If empty, speculative decoding is disabled by default.
The default draft token count to use when creating a deployment. Must be specified if default_draft_model is specified.
The resource name of the BYOC cluster to which this model belongs. e.g. accounts/my-account/clusters/my-cluster. Empty if it belongs to a Fireworks cluster.
If true, the model is calibrated and can be deployed to non-FP16 precisions.
If true, the model can be fine-tuned. The value will be true if the tunable field is true, and the model is validated against the model_type field.
Whether this model supports LoRA.
If true, the model will use the Hugging Face apply_chat_template API to apply the chat template.
The update time for the model.
A json object that contains the default sampling parameters for the model.
If true, the model is RL tunable.
The maximum context length supported by the model.
If true, the model has a serverless deployment.
Response
A successful response.
Human-readable display name of the model. e.g. "My Model" Must be fewer than 64 characters long.
The description of the model. Must be fewer than 1000 characters long.
The creation time of the model.
- UPLOADING: The model is still being uploaded (upload is asynchronous).
- READY: The model is ready to be used.
- HF_BASE_MODEL: An LLM base model.
- HF_PEFT_ADDON: A parameter-efficent fine-tuned addon.
- HF_TEFT_ADDON: A token-eficient fine-tuned addon.
- FLUMINA_BASE_MODEL: A Flumina base model.
- FLUMINA_ADDON: A Flumina addon.
- DRAFT_ADDON: A draft model used for speculative decoding in a deployment.
- FIRE_AGENT: A FireAgent model.
- LIVE_MERGE: A live-merge model.
- CUSTOM_MODEL: A customized model
- EMBEDDING_MODEL: An Embedding model.
- SNAPSHOT_MODEL: A snapshot model.
The URL to GitHub repository of the model.
The URL to the Hugging Face model.
If true, the model will be publicly readable.
The maximum context length supported by the model.
If set, images can be provided as input to the model.
If set, tools (i.e. functions) can be provided as input to the model, and the model may respond with one or more tool calls.
The name of the the model from which this was imported. This field is empty if the model was not imported.
If the model was created from a fine-tuning job, this is the fine-tuning job name.
The default draft model to use when creating a deployment. If empty, speculative decoding is disabled by default.
The default draft token count to use when creating a deployment. Must be specified if default_draft_model is specified.
The resource name of the BYOC cluster to which this model belongs. e.g. accounts/my-account/clusters/my-cluster. Empty if it belongs to a Fireworks cluster.
If true, the model is calibrated and can be deployed to non-FP16 precisions.
If true, the model can be fine-tuned. The value will be true if the tunable field is true, and the model is validated against the model_type field.
Whether this model supports LoRA.
If true, the model will use the Hugging Face apply_chat_template API to apply the chat template.
The update time for the model.
A json object that contains the default sampling parameters for the model.
If true, the model is RL tunable.
The maximum context length supported by the model.
If true, the model has a serverless deployment.