bertin-project/bertin-gpt-j-6B-boe-summaries
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BERTIN Project
non-profit
AI & ML interests
Pre-training and evaluation of BERT-based language models for Spanish. More information at https://huggingface.co./bertin-project/bertin-roberta-base-spanish
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versae
updated
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8 days ago
Adding `safetensors` variant of this model
#1 opened 9 days ago
by
SFconvertbot
versae
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models
9 days ago
versae
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paper
13 days ago
Adding `safetensors` variant of this model
#5 opened about 2 months ago
by
SFconvertbot
versae
updated
a
dataset
about 2 months ago
Missing "languages" kwarg error
2
#6 opened over 1 year ago
by
neo-nlp-dev
mariagrandury
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3 months ago
versae
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3 months ago
versae
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4 months ago
mariagrandury
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5 months ago
versae
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5 months ago
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🚨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/
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mariagrandury
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paper
6 months ago
versae
updated
a
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6 months ago