Firectl
Create a fine-tuning job
Firectl
Create a fine-tuning job
Create a fine-tuning job with a base model
Creates a fine-tuning job on Fireworks AI platform with the provided configuration yaml.
firectl create fine-tuning-job [flags]
Example
firectl create fine-tuning-job --settings-file settings.yaml
Flags
--base-model string (required) The base model used for fine-tuning. e.g. mistralai/Mixtral-8x7B-Instruct-v0.1
--batch-size int32 (optional) The batch size of dataset used for training.
--conversation-template string (optional) The conversation jinja template field.
--dataset string (required) The ID of the dataset for the fine tuning.
--display-name string (optional) The display name of the fine-tuning job.
--draft-base-model string (optional) The draft model hf base model field.
--epochs float (optional) The number of epochs to train for.
--input-template string The input template. Required if kind is text_completion.
--job-id string (optional) The ID of the fine-tuning job.
--kind string (required) The kind of fine-tuning job to run. Must be "text_completion", "text_classification", or "conversation".
--label string The label field. Required is text_classification.
--learning-rate float (optional) The learning rate used for training.
--lora-rank int32 (optional) The LoRA rank used for training.
--model-id string (optional) The ID of the uploaded model.
--output-template string The output template. Required if kind is text_completion.
--settings-file string If specified, the YAML file from which settings should be read.
--text string The text field. Required if kind is text_classification.
-w, --wait Block until the job is complete
-h, --help help for deployment
--wandb-api-key string (optional) A Weights & Biases API key associated with the entity.
--wandb-entity string (optional) The Weights & Biases entity where training progress should be reported.
--wandb-project string (optional) The Weights & Biases project where training progress should be reported.
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