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Alessandro Ercolani

giux78

https://alessandroercolani.webflow.io/

AI & ML interests

NLP, Reinforcement Learning, Semantics, Computational Neuroscience

Recent Activity

liked a Space 2 days ago

evalitahf/evalita_llm_leaderboard

reacted to tomaarsen's post with 🔥 7 days ago

‼️Sentence Transformers v4.0 is out! You can now train and finetune reranker models with multi-GPU training, bf16 support, loss logging, callbacks & much more. I also prove that finetuning on your domain helps much more than you might think. 1️⃣ Reranker Training Refactor Reranker models can now be trained using an extensive trainer with a lot of powerful features: - MultiGPU Training (Data Parallelism (DP) and Distributed Data Parallelism (DDP)) - bf16 training support; loss logging - Evaluation datasets + evaluation loss - Improved callback support + an excellent Weights & Biases integration - Gradient checkpointing, gradient accumulation - Model card generation - Resuming from a training checkpoint without performance loss - Hyperparameter Optimization and much more! Read my detailed blogpost to learn about the components that make up this new training approach: https://huggingface.co/blog/train-reranker Notably, the release is fully backwards compatible: all deprecations are soft, meaning that they still work but emit a warning informing you how to upgrade. 2️⃣ New Reranker Losses - 11 new losses: - 2 traditional losses: BinaryCrossEntropy and CrossEntropy - 2 distillation losses: MSE and MarginMSE - 2 in-batch negatives losses: MNRL (a.k.a. InfoNCE) and CMNRL - 5 learning to rank losses: Lambda, p-ListMLE, ListNet, RankNet, ListMLE 3️⃣ New Reranker Documentation - New Training Overview, Loss Overview, API Reference docs - 5 new, 1 refactored training examples docs pages - 13 new, 6 refactored training scripts - Migration guides (2.x -> 3.x, 3.x -> 4.x) 4️⃣ Blogpost Alongside the release, I've written a blogpost where I finetune ModernBERT on a generic question-answer dataset. My finetunes easily outperform all general-purpose reranker models, even models 4x as big. Finetuning on your domain is definitely worth it: https://huggingface.co/blog/train-reranker See the full release notes here: https://github.com/UKPLab/sentence-transformers/releases/v4.0.1

reacted to their post with 👀 9 days ago

This is truly an inspirational story please help us spread the word, @clem , @thomwolf and everyone who supports open source AI. A few weeks ago, @mmuffo94 and @cittiberto from indigo_ai launched the Chatbot Arena for the Italian language: https://indigo.ai/it/chatbot-arena-italia/. To our surprise, among the top-ranked models is https://huggingface.co/mii-llm/maestrale-chat-v0.4-beta a carefully fine-tuned version of https://huggingface.co/mistralai/Mistral-7B-v0.1, developed by @efederici and @mferraretto from https://huggingface.co/mii-llm, and released nearly a year ago. At this very moment, as shown in the screenshot, https://huggingface.co/mii-llm/maestrale-chat-v0.4-beta is ranked 8th right between ChatGPT-4.5 and ChatGPT-4o. It's likely that for several months, the best Italian speaking LLM has been an open source 7B model created by open source contributors and hardly anyone knew it.

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mii-llm , and released nearly a year ago.

At this very moment, as shown in the screenshot, mii-llm/maestrale-chat-v0.4-beta is ranked 8th right between ChatGPT-4.5 and ChatGPT-4o.

It's likely that for several months, the best Italian speaking LLM has been an open source 7B model created by open source contributors and hardly anyone knew it.

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