Check-out the leaderboard here: https://<strong>huggingface</strong>.co/spaces/ArtificialAnalysis/Text-to-Image-Leaderboard

Launching the Artificial Analysis Text to Image Leaderboard & Arena

Transformers have rapidly become the preferred choice for audio classification, surpassing methods based on CNNs. However, Audio Spectrogram Transformers (ASTs) exhibit quadratic scaling due to self-attention. The removal of this quadratic self-attention cost presents an appealing direction.

Paper page - Audio Mamba: Bidirectional State Space Model for Audio Representation Learning

Significant advancements in video diffusion models have brought substantial progress to the field of text-to-video (T2V) synthesis. However, existing T2V synthesis model struggle to accurately generate complex motion dynamics, leading to a reduction in video realism.

Paper page - Searching Priors Makes Text-to-Video Synthesis Better

Discover amazing ML apps made by the community

starline - a Hugging Face Space by mattyamonaca

Stableaudio Open 1.0 - a Hugging Face Space by ameerazam08

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

stabilityai/stable-audio-open-1.0 · Hugging Face

We explore uncertainty quantification in large language models (LLMs), with the goal to identify when uncertainty in responses given a query is large. We simultaneously consider both epistemic and aleatoric uncertainties, where the former comes from the lack of knowledge about the ground truth ...

Paper page - To Believe or Not to Believe Your LLM

Text-to-video generation has lagged behind text-to-image synthesis in quality and diversity due to the complexity of spatio-temporal modeling and limited video-text datasets. This paper presents I4VGen, a training-free and plug-and-play video diffusion inference framework, which enhances ...

Paper page - I4VGen: Image as Stepping Stone for Text-to-Video Generation

Recently video diffusion models have emerged as expressive generative tools for high-quality video content creation readily available to general users. However, these models often do not offer precise control over camera poses for video generation, limiting the expression of cinematic language ...

Paper page - CamCo: Camera-Controllable 3D-Consistent Image-to-Video Generation

MODEL_ID = &quot;mlabonne/Daredevil-8B&quot; MODEL_TYPE = &quot;meta-llama/Meta-Llama-3-8B-Instruct&quot; # Download and load model !git clone https://<strong>huggingface</strong>.co/{MODEL_ID} {MODEL_TYPE} # Load model and tokenizer model = HookedTransformer.from_pretrained_no_processing( MODEL_TYPE, local_files_only=True, ...

Uncensor any LLM with abliteration

HuggingFace

 We’ll explore what Hugging Face offers, how to use its resources, and how it’s transforming the field of artificial intelligence.

Here's How the Pros Use Hugging Face to Run Countless AI Models on their PCs

 Spectral is collaborating with deep learning experts from Hugging Face to advance open-source models, datasets, and applications for the Onchain Agent Economy.

Spectral Labs Joins Hugging Face’s ESP Program: Advancing The Onchain x Open-Source AI Community

This article explains the difference between two AI platforms: Eden AI and Hugging Face.

Eden AI vs Hugging Face: Use Cases,  Target Users and Value Propositions 

In this blog, I will show you how to quickly create an entirely free app using a JavaScript program that runs within the free Oracle database and calls Hugging 

Calling Hugging Face AI From an Oracle Database Using JavaScript

Hugging Face offers solutions and tools for developers and researchers. This article looks at the Best Hugging Face Datasets for Building NLP Models.

10 Best Hugging Face Datasets for Building NLP Models

The Datasets library from hugging Face provides a very efficient way to load and process NLP datasets from raw files or in-memory data. These NLP datasets have been shared by different research and practitioner communities across the world.

NLP Datasets from HuggingFace: How to Access and Train Them

How to fine-tune a Hugging Face Transformer model for Sequence Classification

How to Fine Tune a 🤗 (Hugging Face) Transformer Model

Transformer-based models are a game-changer when it comes to using unstructured text data. As of September 2020, the top-performing models in the General Language Understanding Evaluation (GLUE) benchmark are all BERT transformer-based models. At Georgian, we often encounter scenarios where we have supporting tabular feature information and unstructured text data. We found that by using the tabular data in these models, we could further improve performance, so we set out to build a toolkit that makes it easier for others to do the same.

A Beginner Guide to Incorporating Tabular Data via HuggingFace Transformers

Get the most recent info and news about HuggingFace on HackerNoon, where 10k+ technologists publish stories for 4M+ monthly readers.

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HUGGINGFACE

huggingface.co

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Since 2016

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