Add embeddings and search file support #35
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hallacy
commented
Sep 30, 2021
hallacy
commented
- Adds support for the embeddings endpoint
- Add search.prepare_data to the CLI to validate search files for upload
* Add validators for search files * Clean up fields
rachellim
reviewed
Oct 1, 2021
| "-f", | ||
| "--file", | ||
| required=True, | ||
| help="JSONL, JSON, CSV, TSV, TXT or XLSX file containing prompt-completion examples to be analyzed." |
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Copy pasta of prompt-completion from fine tuning?
| sub.add_argument( | ||
| "-p", | ||
| "--purpose", | ||
| help="Why are you uploading this file? (see https://beta.openai.com/docs/api-reference/ for purposes)", |
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It seems unintuitive to me that the Search purpose (which is what this is ostensibly under) is further split into different purposes. Maybe each of them should be a different tool instead? (Or do they all fall under the search umbrella, and how? We can chat outside this PR if i'm missing some context)
|
I think we're gonna split the validation code from the embeddings code. Closing this request down |
pull bot
referenced
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in mcx/openai-python
Oct 10, 2021
* Add CLI option to download files (#34) * Option to check if file has been uploaded in the past before uploading (#33) The check is done based on filename, file purpose and file size * Add fine-tuning hparams directly into the fine-tunes CLI (#35) * update fine_tunes cli use_packing argument (#38) * A file verification and remediation tool. It applies the following validations: - prints the number of examples, and warns if it's lower than 100 - ensures prompt and completion columns are present - optionally removes any additional columns - ensures all completions are non-empty - infers which type of fine-tuning the data is most likely in (classification, conditional generation and open-ended generation) - optionally removes duplicate rows - infers the existence of a common suffix, and if there is none, suggests one for classification and conditional generation - optionally prepends a space to each completion, to make tokenization better - optionally splits into training and validation set for the classification use case - optionally ensures there's an ending string for all completions - optionally lowercases completions or prompts if more than a 1/3 of alphanumeric characters are upper case It interactively asks the user to accept or reject recommendations. If the user is happy, then it saves the modified output file as a jsonl, which is ready for being used in fine-tuning with the printed command. * Completion: remove from kwargs before passing to EngineAPI (#37) * Version bump before pushing to external Co-authored-by: Todor Markov <[email protected]> Co-authored-by: Boris Power <[email protected]> Co-authored-by: Dave Cummings <[email protected]>
cgayapr
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Dec 14, 2024
* Add CLI option to download files (openai#34) * Option to check if file has been uploaded in the past before uploading (openai#33) The check is done based on filename, file purpose and file size * Add fine-tuning hparams directly into the fine-tunes CLI (openai#35) * update fine_tunes cli use_packing argument (openai#38) * A file verification and remediation tool. It applies the following validations: - prints the number of examples, and warns if it's lower than 100 - ensures prompt and completion columns are present - optionally removes any additional columns - ensures all completions are non-empty - infers which type of fine-tuning the data is most likely in (classification, conditional generation and open-ended generation) - optionally removes duplicate rows - infers the existence of a common suffix, and if there is none, suggests one for classification and conditional generation - optionally prepends a space to each completion, to make tokenization better - optionally splits into training and validation set for the classification use case - optionally ensures there's an ending string for all completions - optionally lowercases completions or prompts if more than a 1/3 of alphanumeric characters are upper case It interactively asks the user to accept or reject recommendations. If the user is happy, then it saves the modified output file as a jsonl, which is ready for being used in fine-tuning with the printed command. * Completion: remove from kwargs before passing to EngineAPI (openai#37) * Version bump before pushing to external Co-authored-by: Todor Markov <[email protected]> Co-authored-by: Boris Power <[email protected]> Co-authored-by: Dave Cummings <[email protected]>
safa0
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Apr 27, 2025
docs: Fix typos in documentation files
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