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Large Language Diffusion with Masking (LLaDA) are here - and their generation looks so fucking dope! 🤯 True to Yann LeCun's vision, Ditch the auto-regressive bits and approximate the language distribution via Maximum Likelihood Estimation! So cool to watch the model denoise text from tokens in real time! -... show more

Vaibhav (VB) Srivastav

43,377 subscribers

21,394 Aufrufe • vor 1 Jahr •via X (Twitter)

Wissenschaft & Technologie

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Profilbild von Vaibhav (VB) Srivastav

Vaibhav (VB) Srivastavvor 1 Jahr

Check out the demo here:

Profilbild von Vaibhav (VB) Srivastav

Vaibhav (VB) Srivastavvor 1 Jahr

Model checkpoints here:

Profilbild von AssemblyAI

AssemblyAIvor 1 Jahr

Announcing: Our most advanced speech-to-text model goes beyond accuracy to capture the real-world complexity of human conversation and deliver reliable, source-of-truth audio data. Explore Universal-2 updates 👇

Profilbild von Chaithanya Kumar

Chaithanya Kumarvor 1 Jahr

@ylecun @Stardust_nds check this out buddy , something that we have been discussing about Also LLaDa

Profilbild von HosseinAgha

HosseinAghavor 1 Jahr

@ylecun This is interesting! Finally a new architecture for LLMs. I don't think this solves any of the @ylecun concerns with transformer based Auto Regressive LMs. No world model. No video understanding, etc.

Profilbild von luis

luisvor 1 Jahr

@ylecun Omg , I think this idea is perfect to make the answers more precise, 🥵 hello 100 precision

Profilbild von marko.

marko.vor 1 Jahr

@ylecun Since you have to compute the whole maximum possible response length every time, what does this mean for VRAM requirements when deploying these models?

Profilbild von Futurist Avenue

Futurist Avenuevor 1 Jahr

@ylecun How does this stack up with Inception?

Profilbild von AI at Meta

AI at Metavor 1 Jahr

Llama has now been downloaded over 1 Billion times! A note to: The researchers at Meta training these models — and those building on the research in other labs. The developers and enthusiasts on r/LocalLlama, @huggingface and more; experimenting with new models and creating derivatives. The small startups and big enterprises alike who are creating a new wave of AI-powered products, built with Llama. The global AI community. Your actions speak louder than words, thank you for making it abundantly clear — a billion times over — that open source AI is how we'll create the next wave of world changing technologies, together. 🦙❤️

Profilbild von Hunyuan

Hunyuanvor 1 Jahr

Coming soon: HunYuan-T1，The first ultra-large Mamba-powered reasoning model! Stay tuned! 🚀

Profilbild von AK

AKvor 1 Jahr

Bytedance just dropped DAPO on Hugging Face An Open-Source LLM Reinforcement Learning System at Scale

Profilbild von Jeremy Howard

Jeremy Howardvor 1 Jahr

Announcing fasttransform: a Python lib that makes data transformations reversible/extensible. No more writing inverse functions to see what your model sees. Debug pipelines by actually looking at your data. Built on multi-dispatch. Work w/ @R_Dimm

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Tanishq Mathew Abraham, Ph.D.

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Google presents AudioPaLM: A Large Language Model That Can Speak and Listen paper page: introduce AudioPaLM, a large language model for speech understanding and generation. AudioPaLM fuses text-based and speech-based language models, PaLM-2 [Anil et al., 2023] and AudioLM [Borsos et al., 2022], into a unified multimodal architecture that can process and generate text and speech with applications including speech recognition and speech-to-speech translation. AudioPaLM inherits the capability to preserve paralinguistic information such as speaker identity and intonation from AudioLM and the linguistic knowledge present only in text large language models such as PaLM-2. We demonstrate that initializing AudioPaLM with the weights of a text-only large language model improves speech processing, successfully leveraging the larger quantity of text training data used in pretraining to assist with the speech tasks. The resulting model significantly outperforms existing systems for speech translation tasks and has the ability to perform zero-shot speech-to-text translation for many languages for which input/target language combinations were not seen in training. AudioPaLM also demonstrates features of audio language models, such as transferring a voice across languages based on a short spoken prompt.

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SIKAOFFICIAL🦍

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