# Docs for v2 can be found by changing the above selector ^
from together import Together
import os
client = Together(
api_key=os.environ.get("TOGETHER_API_KEY"),
)
response = client.fine_tuning.list()
for fine_tune in response.data:
print(f"ID: {fine_tune.id}, Status: {fine_tune.status}"){
"data": [
{
"id": "ft-01234567890123456789",
"status": "completed",
"created_at": "2023-05-17T17:35:45.123Z",
"updated_at": "2023-05-17T18:46:23.456Z",
"user_id": "user_01234567890123456789",
"owner_address": "[email protected]",
"total_price": 1500,
"token_count": 850000,
"events": [],
"model": "meta-llama/Llama-2-7b-hf",
"model_output_name": "mynamespace/meta-llama/Llama-2-7b-hf-32162631",
"n_epochs": 3,
"training_file": "file-01234567890123456789",
"wandb_project_name": "my-finetune-project"
}
]
}List All Jobs
List the metadata for all fine-tuning jobs. Returns a list of FinetuneResponseTruncated objects.
# Docs for v2 can be found by changing the above selector ^
from together import Together
import os
client = Together(
api_key=os.environ.get("TOGETHER_API_KEY"),
)
response = client.fine_tuning.list()
for fine_tune in response.data:
print(f"ID: {fine_tune.id}, Status: {fine_tune.status}"){
"data": [
{
"id": "ft-01234567890123456789",
"status": "completed",
"created_at": "2023-05-17T17:35:45.123Z",
"updated_at": "2023-05-17T18:46:23.456Z",
"user_id": "user_01234567890123456789",
"owner_address": "[email protected]",
"total_price": 1500,
"token_count": 850000,
"events": [],
"model": "meta-llama/Llama-2-7b-hf",
"model_output_name": "mynamespace/meta-llama/Llama-2-7b-hf-32162631",
"n_epochs": 3,
"training_file": "file-01234567890123456789",
"wandb_project_name": "my-finetune-project"
}
]
}Authorizations
Bearer authentication header of the form Bearer <token>, where <token> is your auth token.
Response
List of fine-tune jobs
Show child attributes
Show child attributes
Unique identifier for the fine-tune job
pending, queued, running, compressing, uploading, cancel_requested, cancelled, error, completed Creation timestamp of the fine-tune job
Last update timestamp of the fine-tune job
Identifier for the user who created the job
Owner address information
Total price for the fine-tuning job
Count of tokens processed
Events related to this fine-tune job
Show child attributes
Show child attributes
fine-tune-event job_pending, job_start, job_stopped, model_downloading, model_download_complete, training_data_downloading, training_data_download_complete, validation_data_downloading, validation_data_download_complete, wandb_init, training_start, checkpoint_save, billing_limit, epoch_complete, training_complete, model_compressing, model_compression_complete, model_uploading, model_upload_complete, job_complete, job_error, cancel_requested, job_restarted, refund, warning info, warning, error, legacy_info, legacy_iwarning, legacy_ierror File-ID of the training file
File-ID of the validation file
Base model used for fine-tuning
Suffix added to the fine-tuned model name
Number of training epochs
Number of evaluations during training
Number of checkpoints saved during training
Batch size used for training
Learning rate used for training
Learning rate scheduler configuration
Show child attributes
Show child attributes
linear, cosine Ratio of warmup steps
Maximum gradient norm for clipping
Weight decay value used
Weights & Biases project name
Weights & Biases run name
Checkpoint used to continue training
Hugging Face Hub repo to start training from
The revision of the Hugging Face Hub model to continue training from
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