The AI community has introduced TinyLlama, a new compact language model that boasts 1.1 billion parameters and is pretrained on 3 trillion tokens for roughly 3 epochs. This model is designed to be efficient and is fully open-source, outperforming its peers in various tasks despite its small size. TinyLlama utilizes the same architecture and tokenizer as its predecessor LLaMA, and incorporates features like Fully Sharded Data Parallel (FSDP), original SwiGLU, and FlashAttention to enhance its efficiency. It also has chat capabilities and can hold conversations. Additionally, the TinyLlama project aims to achieve its pretraining within just 90 days using 16 A100-40G GPUs. In a similar vein, LiteLlama has been released as an open-source reproduction of Meta AI's LLaMA 2, but with a reduced model size of 460 million parameters, also trained on 1 trillion tokens. Both models represent significant strides in AI, aiming to provide powerful capabilities in more compact and efficient packages.
TinyLlama: An Open-Source Small Language Model https://t.co/fphyTajlGg
TinyLlama: An Open-Source Small Language Model https://t.co/RtEOFU2cm8
TinyLlama chat demo is out https://t.co/0wMSxEW2gj The TinyLlama project aims to pretrain a 1.1B Llama model on 3 trillion tokens. With some proper optimization, we can achieve this within a span of "just" 90 days using 16 A100-40G GPUs https://t.co/nXBDk0PmJW
Meet TinyLlama: An Open-Source Small-Scale Language Model that Pretrain a 1.1B Llama Model on 3 Trillion Tokens Quick read: https://t.co/xLea9gujyk Paper: https://t.co/MGdYdehoza Github: https://t.co/9YoXqWuSxK #ArtificialIntelligence #LLMs https://t.co/nhxdaFIZRo
Step into the future with #LiteLlama, a groundbreaking AI model mirroring the prowess of Meta AI's LLaMa 2 but in a more compact form! 🚀 With a sleek 460M parameters, trained on an impressive 1T tokens, LiteLlama-460M-1T offers an efficient yet powerful AI experience. Developed… https://t.co/Pc0wRr0dO3
LiteLlama is out an open-source reproduction of Meta AI's LLaMa 2. However, with significantly reduced model sizes, LiteLlama-460M-1T has 460M parameters trained with 1T tokens. https://t.co/qRtKo81oSo https://t.co/gq9TGEax8m
Can We Transfer the Capabilities of LLMs like LLaMA from English to Non-English Languages? A Deep Dive into Multilingual Model Proficiency Quick read: https://t.co/tFTLPFhbEW Paper: https://t.co/NC0hXDSXhP #ArtificialInteligence https://t.co/y8uMRjlC0T
[CL] TinyLlama: An Open-Source Small Language Model https://t.co/Ccr3yiy65M TinyLlama is an open-source small language model that achieves remarkable performance despite its relatively small size. It surpasses existing models of similar sizes in various downstream tasks. It… https://t.co/5MIzIvJb2P
Read the paper for TinyLLaMA today 🦙💗 https://t.co/qRydmAY73W Some highlights ✨ - It's a 1.1B LM pre-trained on 1T tokens for 3 epochs - It really is a compact version of LLaMA, same architecture and tokenizer - Uses FSDP, original SwiGLU and FlashAttention for efficiency… https://t.co/VXHEouAfMI
Discover TinyLlama, the new small language model with big performance gains. Outshines peers in tasks while remaining efficient and fully open-source: https://t.co/oZgwRBNN0T https://t.co/sBu0r6i5QU
TinyLlama: An Open-Source Small Language Model paper page: https://t.co/XRI6xeGzYI present TinyLlama, a compact 1.1B language model pretrained on around 1 trillion tokens for approximately 3 epochs https://t.co/DGX9imUNyv
TinyLlama: An Open-Source Small Language Model Presents a compact 1.1B LM pretrained on around 1T tokens for ~3 epochs repo: https://t.co/nR4X7Hmsy2 abs: https://t.co/ted3gpL8ii https://t.co/RMEABiHsPg
tinyllama is a 1.1B parameter model trained on 3T tokens. it now knows how to chat and can hold a conversation. model links and more... 👇 https://t.co/EaCkfI4Bqv