ML Research Hub – Telegram
ML Research Hub
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Advancing research in Machine Learning – practical insights, tools, and techniques for researchers.

Admin: @HusseinSheikho || @Hussein_Sheikho
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🖥 TORCH UNCERTAINTY

Comprehensive PyTorch Library for deep learning uncertainty quantification techniques.

pip install torch-uncertainty

🖥 Github: https://github.com/ensta-u2is/torch-uncertainty

📕 Paper: https://arxiv.org/abs/2311.01434v1

Project: https://llmrec.github.io/

👣 Api: https://torch-uncertainty.github.io/api.html

🌐 Dataset: https://paperswithcode.com/dataset/cifar-10

https://news.1rj.ru/str/DataScienceT
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PETA: Evaluating the Impact of Protein Transfer Learning with Sub-word Tokenization on Downstream Applications

🖥 Github: https://github.com/ginnm/proteinpretraining

📕 Paper: https://arxiv.org/pdf/2310.17415v1.pdf

🔥 Datasets: https://paperswithcode.com/dataset/peta-protein

Tasks: https://paperswithcode.com/task/language-modelling

https://news.1rj.ru/str/DataScienceT
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🎧 Video2Music: Suitable Music Generation from Videos using an Affective Multimodal Transformer model

Video2Music: Suitable Music Generation from Videos using an Affective Multimodal Transformer model.

🖥 Github: https://github.com/amaai-lab/video2music

📕 Paper: https://arxiv.org/abs/2311.00968v1

Demo: https://llmrec.github.io/

🌐 Dataset: https://zenodo.org/records/10057093

https://news.1rj.ru/str/DataScienceT
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Top execs from billion-dollar giants are whispering about next crypto "GEM". Want in?

This Tuesday, Blockchain Whispers pulls back the curtain. Join the insiders now: https://news.1rj.ru/str/+c5yEZuGFtsc5NDlk
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Bilingual Corpus Mining and Multistage Fine-Tuning for Improving Machine Translation of Lecture Trannoscripts

🖥 Github: https://github.com/shyyhs/CourseraParallelCorpusMining

📕 Paper: https://arxiv.org/abs/2311.03696v1

🔥 Datasets: https://paperswithcode.com/dataset/aspec

https://news.1rj.ru/str/DataScienceT
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Large Language Models (in 2023)

An excellent summary of the research progress and developments in LLMs.

Hyung Won chung, OpenAI (ex.Google and MIT Alumni) made this content publicly available. It's a great way to catch up on some important themes like scaling and optimizing LLMs.

Watch his talk here and Slides shared here.

https://news.1rj.ru/str/DataScienceT
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🚀 Whisper-V3 / Consistency Decoder

Improved decoding for stable diffusion vaes.

- Whisper paper: https://arxiv.org/abs/2212.04356
- Whisper-V3 checkpoint: https://github.com/openai/whisper/discussions/1762
- Consistency Models: https://arxiv.org/abs/2303.01469
- Consistency Decoder release: https://github.com/openai/consistencydecoder

https://news.1rj.ru/str/DataScienceT
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NVIDIA just made Pandas 150x faster with zero code changes.

All you have to do is:
%load_ext cudf.pandas
import pandas as pd


Their RAPIDS library will automatically know if you're running on GPU or CPU and speed up your processing.

You can try it in this colab notebook

GitHub repo: https://github.com/rapidsai/cudf

https://news.1rj.ru/str/DataScienceT
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🪞 Mirror: A Universal Framework for Various Information Extraction Tasks

🖥 Github: https://github.com/Spico197/Mirror

📕 Paper: https://arxiv.org/abs/2311.05419v1

🌐 Dataset: https://paperswithcode.com/dataset/glue

https://news.1rj.ru/str/DataScienceT
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⚡️ LCM-LoRA: A Universal Stable-Diffusion Acceleration Module

Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference.

pip install diffusers transformers accelerate gradio==3.48.0

🖥 Github: https://github.com/luosiallen/latent-consistency-model

📕 Paper: https://arxiv.org/abs/2311.05556v1

🌐 Project: https://latent-consistency-models.github.io

🤗 Demo: https://huggingface.co/spaces/SimianLuo/Latent_Consistency_Model

https://news.1rj.ru/str/DataScienceT
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Perhaps you have thought about placing ads on it?

To do this, follow three simple steps:

1) Sign up: https://telega.io/c/dataScienceT
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If the topic of your post fits our channel, we will publish it with pleasure.
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🔊 Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models

Сhat & pretrained large audio language model proposed by Alibaba Cloud.

🐱 Github: https://github.com/qwenlm/qwen-audio

🚀 Demo: https://qwen-audio.github.io/Qwen-Audio/

📕 Paper: https://arxiv.org/abs/2311.07919v1

Dataset: https://paperswithcode.com/dataset/vocalsound

https://news.1rj.ru/str/DataScienceT
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