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A few weeks ago, we uploaded the MERIT Dataset 🎒📃🏆 into Hugging Face 🤗!
A few weeks ago, we uploaded the MERIT Dataset 🎒📃🏆 into Hugging Face 🤗!
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Now, we are excited to share the Merit Dataset paper via arXiv! 📃💫
Now, we are excited to share the Merit Dataset paper via arXiv! 📃💫
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resource
https://huggingface.co/papers/2409.00447
paper
2409.00447
https://huggingface.co/papers/2409.00447
The MERIT Dataset: Modelling and Efficiently Rendering Interpretable
  Transcripts (2409.00447)
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The MERIT Dataset is a fully synthetic, labeled dataset created for training and benchmarking LLMs on Visually Rich Document Understanding tasks. It is also designed to help detect biases and improve interpretability in LLMs, where we are actively working. 🔧🔨
The MERIT Dataset is a fully synthetic, labeled dataset created for training and benchmarking LLMs on Visually Rich Document Understanding tasks. It is also designed to help detect biases and improve interpretability in LLMs, where we are actively working. 🔧🔨
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MERIT contains synthetically rendered students' transcripts of records from different schools in English and Spanish. We plan to expand the dataset into different contexts (synth medical/insurance documents, synth IDS, etc.) Want to collaborate? Do you have any feedback? 🧐
MERIT contains synthetically rendered students' transcripts of records from different schools in English and Spanish. We plan to expand the dataset into different contexts (synth medical/insurance documents, synth IDS, etc.) Want to collaborate? Do you have any feedback? 🧐
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Resources:
Resources:
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- Dataset: 
- Dataset: 
resource
https://huggingface.co/datasets/de-Rodrigo/merit
dataset
de-Rodrigo/merit
https://huggingface.co/datasets/de-Rodrigo/merit
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- Code and generation pipeline: 
- Code and generation pipeline: 
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https://github.com/nachoDRT/MERIT-Dataset
https://github.com/nachoDRT/MERIT-Dataset
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PD: We are grateful to Hugging Face 🤗 for providing the fantastic tools and resources we find in the platform and, more specifically, to 
PD: We are grateful to Hugging Face 🤗 for providing the fantastic tools and resources we find in the platform and, more specifically, to 
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@nielsr
nielsr
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 for sharing the fine-tuning/inference scripts we have used in our benchmark.
 for sharing the fine-tuning/inference scripts we have used in our benchmark.
A few weeks ago, we uploaded the MERIT Dataset 🎒📃🏆 into Hugging Face 🤗!

Now, we are excited to share the Merit Dataset paper via arXiv! 📃💫
https://huggingface.co/papers/2409.00447

The MERIT Dataset is a fully synthetic, labeled dataset created for training and benchmarking LLMs on Visually Rich Document Understanding tasks. It is also designed to help detect biases and improve interpretability in LLMs, where we are actively working. 🔧🔨

MERIT contains synthetically rendered students' transcripts of records from different schools in English and Spanish. We plan to expand the dataset into different contexts (synth medical/insurance documents, synth IDS, etc.) Want to collaborate? Do you have any feedback? 🧐

Resources:

- Dataset: https://huggingface.co/datasets/de-Rodrigo/merit
- Code and generation pipeline: https://github.com/nachoDRT/MERIT-Dataset

PD: We are grateful to Hugging Face 🤗 for providing the fantastic tools and resources we find in the platform and, more specifically, to @nielsr for sharing the fine-tuning/inference scripts we have used in our benchmark.
👀
John6666 louisbrulenaudet
🔥
David-Egea