firectl create supervised-fine-tuning-job

firectl create supervised-fine-tuning-job [flags]

firectl create sftj \
	--base-model llama-v3-8b-instruct \
	--dataset sample-dataset \
	--output-model name-of-the-trained-model

      --base-model string                   The base model for the supervised fine-tuning job. Only one of base-model or warm-start-from should be specified.
      --dataset string                      The dataset for the supervised fine-tuning job. (Required)
      --output-model string                 The output model for the supervised fine-tuning job.
      --job-id string                       The ID of the supervised fine-tuning job. If not set, it will be autogenerated.
      --warm-start-from string              The model to warm start from. If set, base-model must not be set.
      --evaluation-dataset string           The evaluation dataset for the supervised fine-tuning job.
      --epochs int32                        The number of epochs for the supervised fine-tuning job.
      --learning-rate float32               The learning rate for the supervised fine-tuning job.
      --max-context-length int32            Maximum token length for sequences within each training batch. Shorter sequences are concatenated; longer sequences are truncated. (default 8192)
      --batch-size int32                    The maximum number of tokens packed into each training batch. (default 32768)
      --gradient-accumulation-steps int32   The number of gradient accumulation steps for the supervised fine-tuning job. (default 1)
      --learning-rate-warmup-steps int32    The number of learning rate warmup steps for the supervised fine-tuning job.
      --lora-rank int32                     The rank of the LoRA layers for the supervised fine-tuning job.
                                             (default 8)
      --wandb-api-key string                [WANDB_API_KEY] WandB API Key. (Required if any WandB flag is set)
      --wandb-project string                [WANDB_PROJECT] WandB Project. (Required if any WandB flag is set)
      --wandb-entity string                 [WANDB_ENTITY] WandB Entity. (Required if any WandB flag is set)
      --wandb                               Enable WandB
                                            
      --display-name string                 The display name of the supervised fine-tuning job.
      --early-stop                          Enable early stopping for the supervised fine-tuning job.
      --quiet                               If set, only errors will be printed.
      --eval-auto-carveout                  If set, the evaluation dataset will be auto-carved.
      --mtp-enable                          If set, enables MTP (Multi-Token-Prediction) layer (only available for Deepseek finetuning).
      --mtp-num-draft-tokens int32          Number of draft tokens in MTP. Needs to be between 1 and 3. Default is 1.
      --mtp-freeze-base-model               If set, freezes the base model parameters during MTP training.
  -h, --help                                help for supervised-fine-tuning-job

  -a, --account-id string   The Fireworks account ID. If not specified, reads account_id from ~/.fireworks/auth.ini.
      --api-key string      An API key used to authenticate with Fireworks.
      --dry-run             Print the request proto without running it.
  -o, --output Output       Set the output format to "text", "json", or "flag". (default text)
  -p, --profile string      fireworks auth and settings profile to use.