Kaleidoscope: In-language Exams for Massively Multilingual Vision Evaluation
Paper
•
2504.07072
•
Published
•
9
Biomedical TeMU
AI & ML interests
None defined yet.
Recent Activity
View all activity
Biomedical-TeMU's activity
mariagrandury
authored
2
papers
12 days ago
mariagrandury
authored
a
paper
8 months ago
mariagrandury
authored
a
paper
11 months ago
Post
6323
🚨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 (
🤔 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
[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/
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
🔍 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/
- 7 replies
mariagrandury
authored
a
paper
11 months ago
Post
7186
Working on a concept
The ckpt and training code will be soon on the hub.
GPT-2 (small) that uses KANs instead of MLPs.The ckpt and training code will be soon on the hub.
-
- 6 replies
mariagrandury
posted
an
update
over 1 year ago
Post
✅ Ever wondered how to measure transparency in model development?
My last open-source contribution for 2023 is s Space that allows you to self-assess the transparency of your model based on the 100 indicators of the Foundation Model Transparency Index (FMTI).
The original study evaluated the developers of 10 top LLMs. Curious about how yours measures up? 👀
mariagrandury/fmti-transparency-self-assessment
Let's commit to a 2024 with greater transparency in the AI ecosystem! 🚀
My last open-source contribution for 2023 is s Space that allows you to self-assess the transparency of your model based on the 100 indicators of the Foundation Model Transparency Index (FMTI).
The original study evaluated the developers of 10 top LLMs. Curious about how yours measures up? 👀
mariagrandury/fmti-transparency-self-assessment
Let's commit to a 2024 with greater transparency in the AI ecosystem! 🚀
-
- 6 replies
mariagrandury
posted
an
update
over 1 year ago
Post
Holiday talk about AI taking over? Let's shift the narrative!
🌟 There is no reason to believe that just because AI systems are intelligent they will want to dominate us. Yann LeCun reminds us that AI systems won't have the same motivations as humans, we'll design them not to.
🌍 Instead of getting distracted by future existential risks, we must address AI’s more pressing risks — like emitting carbon, infringing copyrights and spreading bias. Sasha Luccioni urges us to create tools and legislation that promote transparency and diversity.
💡 Dive deeper into these perspectives:
- Yann's ( @ylecun ) WIRED interview (12'): https://www.wired.com/story/artificial-intelligence-meta-yann-lecun-interview/
- Sasha's ( @sasha ) TED Talk (10'): https://www.ted.com/talks/sasha_luccioni_ai_is_dangerous_but_not_for_the_reasons_you_think
P.S.: Love this new "Posts" feature, big thanks to 🤗 for letting me try it!
What are your go-to citations for AI risks? 👇
🌟 There is no reason to believe that just because AI systems are intelligent they will want to dominate us. Yann LeCun reminds us that AI systems won't have the same motivations as humans, we'll design them not to.
🌍 Instead of getting distracted by future existential risks, we must address AI’s more pressing risks — like emitting carbon, infringing copyrights and spreading bias. Sasha Luccioni urges us to create tools and legislation that promote transparency and diversity.
💡 Dive deeper into these perspectives:
- Yann's ( @ylecun ) WIRED interview (12'): https://www.wired.com/story/artificial-intelligence-meta-yann-lecun-interview/
- Sasha's ( @sasha ) TED Talk (10'): https://www.ted.com/talks/sasha_luccioni_ai_is_dangerous_but_not_for_the_reasons_you_think
P.S.: Love this new "Posts" feature, big thanks to 🤗 for letting me try it!
What are your go-to citations for AI risks? 👇
- 2 replies
mrm8488
authored
a
paper
almost 2 years ago
mrm8488
authored
a
paper
about 2 years ago
mariagrandury
authored
a
paper
about 2 years ago
espejelomar
authored
a
paper
about 2 years ago
mrm8488
authored
a
paper
about 2 years ago
mariagrandury
authored
a
paper
about 2 years ago
mrm8488
authored
2
papers
about 2 years ago
espejelomar
updated
2
datasets
about 3 years ago