Pere Martra

oopere

AI & ML interests

Author of the Book 'Large Language Models Projects: Apply and Implement Strategies for Large Language Models' published by Apress.

Recent Activity

reacted to burtenshaw's post with 🚀 1 day ago

AGENTS + FINETUNING! This week Hugging Face learn has a whole pathway on finetuning for agentic applications. You can follow these two courses to get knowledge on levelling up your agent game beyond prompts: 1️⃣ New Supervised Fine-tuning unit in the NLP Course https://huggingface.co./learn/nlp-course/en/chapter11/1 2️⃣New Finetuning for agents bonus module in the Agents Course https://huggingface.co./learn/agents-course/bonus-unit1/introduction Fine-tuning will squeeze everything out of your model for how you’re using it, more than any prompt.

updated a model 4 days ago

oopere/Llama-FinSent-S

published a model 13 days ago

oopere/Llama-FinSent-S

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oopere's activity

upvoted an article 18 days ago

Article

Open-R1: a fully open reproduction of DeepSeek-R1

24 days ago

• 767

upvoted an article about 2 months ago

Article

Making LLMs Smaller Without Breaking Them: A GLU-Aware Pruning Approach

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Nov 24, 2024

• 2

upvoted a paper 4 months ago

Shortened LLaMA: A Simple Depth Pruning for Large Language Models

Paper • 2402.02834 • Published Feb 5, 2024 • 16

upvoted 2 articles 7 months ago

Article

Preference Tuning LLMs with Direct Preference Optimization Methods

Jan 18, 2024

• 47

Article

How NuminaMath Won the 1st AIMO Progress Prize

Jul 11, 2024

• 116

upvoted a collection 9 months ago

Preference Datasets for DPO

Collection

This collection contains a list of curated preference datasets for DPO fine-tuning for intent alignment of LLMs • 7 items • Updated Dec 11, 2024 • 39

upvoted an article 9 months ago

Article

🪆 Introduction to Matryoshka Embedding Models

Feb 23, 2024

• 77

upvoted an article 10 months ago

Article

Making LLMs even more accessible with bitsandbytes, 4-bit quantization and QLoRA

May 24, 2023

• 118