Davipar

Davipar

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upvoted a paper 27 days ago

NoLiMa: Long-Context Evaluation Beyond Literal Matching

liked a Space 4 months ago

PR-Puppets/PR-Puppet-Sora

liked a model 4 months ago

mrm8488/distilroberta-finetuned-financial-news-sentiment-analysis

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Davipar's activity

upvoted a paper 27 days ago

NoLiMa: Long-Context Evaluation Beyond Literal Matching

Paper • 2502.05167 • Published Feb 7 • 15

liked a Space 4 months ago

656

PR Puppet Sora

👁

Generate videos from text prompts

liked 2 models 4 months ago

mrm8488/distilroberta-finetuned-financial-news-sentiment-analysis

Text Classification • Updated Jan 21, 2024 • 459k • • 377

si-pbc/hertz-dev

Audio-to-Audio • Updated Nov 14, 2024 • 211

liked a model 5 months ago

MAISAAI/gemma-2b-coder

Text Generation • Updated May 8, 2024 • 73 • 5

liked a Space 5 months ago

1.05k

Open NotebookLM

🎙

Personalised Podcasts For All - Available in 13 Languages

liked a dataset 6 months ago

TIGER-Lab/MMLU-Pro

Viewer • Updated Nov 27, 2024 • 12.1k • 44k • 330

liked a model 6 months ago

mattshumer/Reflection-Llama-3.1-70B

Text Generation • Updated Sep 24, 2024 • 676 • 1.72k

liked a Space 7 months ago

Eagle X5 13B Chat

🚀

Combine text and images to generate responses

reacted to mrm8488's post with ❤️ 8 months ago

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5470

🚨Exciting news for the Multilingual Synthetic Data Community!🚨

I’ve taken inspiration from the MAGPIE paper on Llama-3-8B-instruct and extended its capabilities. Here’s what’s new!

🗞 The MAGPIE paper showcased that if you use the instruction-tuned version (Llama-3-8B-instruct) to generate synthetic instructions and then fine-tune the base version (Llama-3-8B) on this dataset, you can improve even the it-tuned version

🤔 While reading a script by Sebastian Raschka, PhD, I wondered: Could these advancements be replicated in other languages? Specifically, could they benefit non-English datasets?

🎉 And the answer is YES! At least for Spanish. I've successfully adapted the techniques for Spanish, proving the model's flexibility and multilingual capabilities.

👩‍💻 To make this accessible, I created a basic script (heavily inspired by the Sebastian Raschka one) that allows you to generate similar datasets using ollama models (initially phi and llama3) automatically and upload it to the Hugging Face Hub!
[Script](https://gist.github.com/mrm8488/4650a5e3cc45523798a527a3446eb312)

🔍 Explore the datasets 📚 generated using our new script!

- [Llama-3-8B](https://huggingface.co/datasets/mrm8488/dataset_llama3_5000_samples_es_4231_filtered)
- [Phi-3-medium](https://huggingface.co/datasets/mrm8488/dataset_phi3-medium_5000_samples_es_3906_filtered)
- [Phi-3-mini](https://huggingface.co/datasets/mrm8488/dataset_phi3_5000_samples_es_3282_filtered)

Note: These datasets have basic filtering. Apply additional quality filters before using them to fine-tune large language models.

Inspiration and base script:
https://github.com/rasbt/LLMs-from-scratch/blob/main/ch07/05_dataset-generation/llama3-ollama.ipynb
https://www.linkedin.com/feed/update/urn:li:activity:7210982019751661568/