Parag Ekbote PRO

AINovice2005

https://paragekbote.github.io/

AI & ML interests

ML Engineer passionate about taking models from research to production. 1 year supporting tech startups. Active OSS contributor.

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updated a model 1 day ago

AINovice2005/ModernBERT-base-lora-cicflow-1m-r8

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AINovice2005/ModernBERT-base-lora-cicflow-1m-r16

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AINovice2005/ModernBERT-base-lora-cicflow-1m-r4

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updated 3 models 1 day ago

posted an update 2 days ago

Post

I recently created my first storage bucket to store experiment data of my performance analysis of 15 tokenizers across 20 languages.

The setup is simple enough for a new product and can be scalable depending on the use-case 🤗 .

Bucket: https://huggingface.co/buckets/AINovice2005/tokenizer-benchmark

github gist: https://gist.github.com/ParagEkbote/b3877f667f84cbb9a27bdaca94ba662a

Article: https://medium.com/@paragekbote23/one-sentence-fifteen-tokenizers-a-tokenizer-benchmarking-pipeline-with-hf-storage-buckets-2e59790276fd

posted an update 3 days ago

Post

109

I'm pleased to announce that native trackio support has landed in optuna v.4.8.0.

Now you can store HPO trial data to the 🤗 Hub as a dataset: AINovice2005/toy-optuna-hpo-dataset

or Space: AINovice2005/optuna-dashboard

Article which talks about the integration: https://medium.com/@paragekbote23/designing-and-contributing-an-optuna-integration-that-performs-well-in-practice-21a07d77ec2c

posted an update 7 days ago

Post

Pro tip2: You can treat HF datasets as versioned repos by pinning a specific revision (tag, branch or commit) when downloading files. 🧠

This ensures your data processing pipelines always use the exact dataset state before passing the data to the model. It enables reproducible pipelines and allows for reliable outputs of your ML system.

from huggingface_hub import hf_hub_download

data_path = hf_hub_download(
    repo_id="lysandre/arxiv-nlp",
    filename="train.parquet",
    repo_type="dataset",
    revision="877b84a8f93f2d619faa2a6e514a32beef88ab0a"
)

upvoted an article 7 days ago

Article

Ulysses Sequence Parallelism: Training with Million-Token Contexts

10 days ago

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reactedto sdiazlor's post with 🚀 7 days ago

Post

2580

More OSS than ever with the latest pruna 0.3.2 release. It extends existing algorithm families, such as compilers, kernels, and pruners, and adds new ones, including decoders, distillers, enhancers, and recoverers. But it's not only a collection of algorithms; instead, you can easily combine them to get the biggest efficiency win.

Read the full blog here: https://huggingface.co/blog/PrunaAI/pruna-0-3-2-open-source-optimization-algorithms