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sasha authored a paper about 23 hours ago

Fully Autonomous AI Agents Should Not be Developed

lhoestq authored a paper 3 months ago

Croissant: A Metadata Format for ML-Ready Datasets

sasha updated a dataset 3 months ago

rfcx/frugalai

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sasha

authored a paper about 23 hours ago

Fully Autonomous AI Agents Should Not be Developed

Paper • 2502.02649 • Published Feb 4 • 29

lhoestq

authored a paper 3 months ago

Croissant: A Metadata Format for ML-Ready Datasets

Paper • 2403.19546 • Published Mar 28, 2024 • 1

sasha

updated a dataset 3 months ago

rfcx/frugalai

Viewer • Updated Dec 14, 2024 • 50.4k • 77 • 9

lhoestq

posted an update 3 months ago

Post

2013

Made a HF Dataset editor a la gg sheets here: lhoestq/dataset-spreadsheets

With Dataset Spreadsheets:
✏️ Edit datasets in the UI
🔗 Share link with collaborators
🐍 Use locally in DuckDB or Python

Available for the 100,000+ parquet datasets on HF :)

antonyharfield

updated a Space 4 months ago

README

🏃

lhoestq

posted an update 8 months ago

Post

4188

Hey ! I'm working on a 100% synthetic Dataset Hub here (you can search for any kind of datasets an the app invents them). The link is here: infinite-dataset-hub/infinite-dataset-hub

Question for the Community:

Which models should I use to generate images and audio samples for those datasets ? 🤗

4 replies

lhoestq

posted an update 12 months ago

Post

3068

✨ Easy Synthetic Dataset File Generation using LLM DataGen ! Link: https://huggingface.co/spaces/lhoestq/LLM_DataGen

features + how it works:

✍️ Generate the dataset content you want just by entering a file name
💡 Optionally specify the column names you need
💨 The dataset is streamed and generated on-the-fly in JSON Lines format
✅ Generation is constrained to always output valid JSON

How does this work ?
1/ Enter a file name
2/ The model generates column names for such a file. Using structured generation, it can generate 2 to 5 column names using lower case characters and underscores. I use a prompt that asks to generate column names for a realistic dataset and low temperature.
3/ The columns are used to update the Finite State Machine for the dataset content structured generation, so that it is used to generate JSON objects using those columns
4/ The model generates JSON objects using structured generation again, using the updated Finite State Machine. I use a prompt that asks for realistic data and a temperature of 1.

> Why update a Finite State Machine instead of re-creating one ?

Creating one can take up to 30sec, while updating one takes 0.1s (though it requires to manipulate a graph which is not easy to implement)

> Batched generation is faster, why not use it ?

Generate in batches is faster but tends to generate duplicates for this demo.
Further work can be to provide different prompts (one per sequence in the batch) to end up with a different distribution of sequences in each batch. Or implement a custom sampler that would forbid generating the same data in sequences of the same batch.

> How does structured generation work ?

I used the outlines library with transformers to to define a JSON schema that the generation has to follow. It uses a Finite State Machine with token_id as transitions.

Let me know what you think ! And feel free to duplicate/modify it to try other models/prompts or sampling methods :)