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Fix documentation to reference Files API #312

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squeakymouse merged 2 commits into from
Oct 11, 2023
Merged

Fix documentation to reference Files API #312

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cc2111b
Fix documentation to reference Files API
squeakymouse Oct 9, 2023
b24c53c
Merge branch 'main' into katiewu/file-api-documentation-fix
squeakymouse Oct 11, 2023
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5 changes: 4 additions & 1 deletion clients/python/llmengine/file.py
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Expand Up @@ -22,9 +22,12 @@ def upload(cls, file: BufferedReader) -> UploadFileResponse:
"""
Uploads a file to LLM engine.

For use in [FineTune creation](./#llmengine.fine_tuning.FineTune.create), this should be a CSV file with two columns: `prompt` and `response`.
A maximum of 100,000 rows of data is currently supported.

Args:
file (`BufferedReader`):
A file opened with open(file_path, "r")
A local file opened with `open(file_path, "r")`

Returns:
UploadFileResponse: an object that contains the ID of the uploaded file
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10 changes: 6 additions & 4 deletions clients/python/llmengine/fine_tuning.py
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Expand Up @@ -38,8 +38,10 @@ def create(
This API can be used to fine-tune a model. The _model_ is the name of base model
([Model Zoo](../../model_zoo) for available models) to fine-tune. The training
and validation files should consist of prompt and response pairs. `training_file`
and `validation_file` must be publicly accessible HTTP or HTTPS URLs to a CSV file
that includes two columns: `prompt` and `response`. A maximum of 100,000 rows of data is
and `validation_file` must be either publicly accessible HTTP or HTTPS URLs, or
file IDs of files uploaded to LLM Engine's [Files API](./#llmengine.File) (these
will have the `file-` prefix). The referenced files must be CSV files that include
two columns: `prompt` and `response`. A maximum of 100,000 rows of data is
currently supported. At least 200 rows of data is recommended to start to see benefits from
fine-tuning. For sequences longer than the native `max_seq_length` of the model, the sequences
will be truncated.
Expand All @@ -52,10 +54,10 @@ def create(
The name of the base model to fine-tune. See [Model Zoo](../../model_zoo) for the list of available models to fine-tune.

training_file (`str`):
Publicly accessible URL to a CSV file for training. When no validation_file is provided, one will automatically be created using a 10% split of the training_file data.
Publicly accessible URL or file ID referencing a CSV file for training. When no validation_file is provided, one will automatically be created using a 10% split of the training_file data.

validation_file (`Optional[str]`):
Publicly accessible URL to a CSV file for validation. The validation file is used to compute metrics which let LLM Engine pick the best fine-tuned checkpoint, which will be used for inference when fine-tuning is complete.
Publicly accessible URL or file ID referencing a CSV file for validation. The validation file is used to compute metrics which let LLM Engine pick the best fine-tuned checkpoint, which will be used for inference when fine-tuning is complete.

hyperparameters (`Optional[Dict[str, str]]`):
A dict of hyperparameters to customize fine-tuning behavior.
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