source stringlengths 36 80 | text stringlengths 51 500 |
|---|---|
https://en.wikipedia.org/wiki/Transformer_%28deep_learning_architecture%29#146 | Synnaeve, Gabriel (2024). "Better & Faster Large Language Models via Multi-token Prediction". arXiv:2404.19737 [cs.CL].
- ^ DeepSeek-AI; et al. (2024). "DeepSeek-V3 Technical Report". arXiv:2412.19437 [cs.CL].
- ^ a b Kitaev, Nikita; Kaiser, Łukasz; Levskaya, Anselm (2020). "Reformer: The Efficient Transformer". arXiv:... |
https://en.wikipedia.org/wiki/Transformer_%28deep_learning_architecture%29#147 | in Transformer: Hierarchical Vision Transformer using Shifted Windows". 2021 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE. pp. 9992–10002. arXiv:2103.14030. doi:10.1109/ICCV48922.2021.00986. ISBN 978-1-6654-2812-5.
- ^ Ristea, Nicolaea Catalin; Ionescu, Radu Tudor; Khan, Fahad Shahbaz (2022-09-18).... |
https://en.wikipedia.org/wiki/Transformer_%28deep_learning_architecture%29#148 | erspeech.2022-249.
- ^ Tay, Yi; Dehghani, Mostafa; Abnar, Samira; Shen, Yikang; Bahri, Dara; Pham, Philip; Rao, Jinfeng; Yang, Liu; Ruder, Sebastian; Metzler, Donald (2020-11-08). "Long Range Arena: A Benchmark for Efficient Transformers". arXiv:2011.04006 [cs.LG].
- ^ "Reformer: The Efficient Transformer". Google AI B... |
https://en.wikipedia.org/wiki/Transformer_%28deep_learning_architecture%29#149 | quel; Grosse, Roger B (2017). "The Reversible Residual Network: Backpropagation Without Storing Activations". Advances in Neural Information Processing Systems. 30. Curran Associates, Inc. arXiv:1707.04585.
- ^ Child, Rewon; Gray, Scott; Radford, Alec; Sutskever, Ilya (2019-04-23), Generating Long Sequences with Sparse... |
https://en.wikipedia.org/wiki/Transformer_%28deep_learning_architecture%29#150 | . 25 March 2021. Archived from the original on 2021-09-18. Retrieved 2021-05-28.
- ^ Zhai, Shuangfei; Talbott, Walter; Srivastava, Nitish; Huang, Chen; Goh, Hanlin; Zhang, Ruixiang; Susskind, Josh (2021-09-21). "An Attention Free Transformer". arXiv:2105.14103 [cs.LG].
- ^ Peng, Hao; Pappas, Nikolaos; Yogatama, Dani; S... |
https://en.wikipedia.org/wiki/Transformer_%28deep_learning_architecture%29#151 | Krzysztof; Likhosherstov, Valerii; Dohan, David; Song, Xingyou; Gane, Andreea; Sarlos, Tamas; Hawkins, Peter; Davis, Jared; Belanger, David; Colwell, Lucy; Weller, Adrian (2020-09-30). "Masked Language Modeling for Proteins via Linearly Scalable Long-Context Transformers". arXiv:2006.03555 [cs.LG].
- ^ Lu, Kevin; Grove... |
https://en.wikipedia.org/wiki/Transformer_%28deep_learning_architecture%29#152 | ings of the AAAI Conference on Artificial Intelligence. 36 (7): 7628–7636. doi:10.1609/aaai.v36i7.20729. ISSN 2374-3468.
- ^ "Vicuna: An Open-Source Chatbot Impressing GPT-4 with 90%* ChatGPT Quality | LMSYS Org". lmsys.org. Retrieved 2024-08-11.
- ^ Liu, Haotian; Li, Chunyuan; Wu, Qingyang; Lee, Yong Jae (2023-12-15).... |
https://en.wikipedia.org/wiki/Transformer_%28deep_learning_architecture%29#153 | k; Xu, Tao; Brockman, Greg; McLeavey, Christine; Sutskever, Ilya (2022). "Robust Speech Recognition via Large-Scale Weak Supervision". arXiv:2212.04356 [eess.AS].
- ^ Jaegle, Andrew; Gimeno, Felix; Brock, Andrew; Zisserman, Andrew; Vinyals, Oriol; Carreira, Joao (2021-06-22). "Perceiver: General Perception with Iterati... |
https://en.wikipedia.org/wiki/Transformer_%28deep_learning_architecture%29#154 | Catalin; Ding, David; Koppula, Skanda; Zoran, Daniel; Brock, Andrew; Shelhamer, Evan; Hénaff, Olivier (2021-08-02). "Perceiver IO: A General Architecture for Structured Inputs & Outputs". arXiv:2107.14795 [cs.LG].
- ^ "Parti: Pathways Autoregressive Text-to-Image Model". sites.research.google. Retrieved 2024-08-09.
- ^... |
https://en.wikipedia.org/wiki/Transformer_%28deep_learning_architecture%29#155 | Santiago; Kunze, Julius; Erhan, Dumitru (2022-09-29). "Phenaki: Variable Length Video Generation from Open Domain Textual Descriptions".
{{cite journal}}
: Cite journal requires|journal=
(help) - ^ a b Chang, Huiwen; Zhang, Han; Barber, Jarred; Maschinot, A. J.; Lezama, Jose; Jiang, Lu; Yang, Ming-Hsuan; Murphy, Kevin;... |
https://en.wikipedia.org/wiki/Transformer_%28deep_learning_architecture%29#156 | - ^ Ramesh, Aditya; Pavlov, Mikhail; Goh, Gabriel; Gray, Scott; Voss, Chelsea; Radford, Alec; Chen, Mark; Sutskever, Ilya (2021-02-26), Zero-Shot Text-to-Image Generation, arXiv:2102.12092
- ^ Yu, Jiahui; Xu, Yuanzhong; Koh, Jing Yu; Luong, Thang; Baid, Gunjan; Wang, Zirui; Vasudevan, Vijay; Ku, Alexander; Yang, Yinfei... |
https://en.wikipedia.org/wiki/Transformer_%28deep_learning_architecture%29#157 | Alyea, Gioconda; Qu, Sue; Sanjak, Jaleal; Mathé, Ewy; Sid, Eric; Chatelaine, Haley; Yadaw, Arjun; Xu, Yanji; Zhu, Qian (2023). "Precision information extraction for rare disease epidemiology at scale". Journal of Translational Medicine. 21 (1): 157. doi:10.1186/s12967-023-04011-y. PMC 9972634. PMID 36855134.
Further re... |
https://en.wikipedia.org/wiki/Transformer_%28deep_learning_architecture%29#158 | 18
- Phuong, Mary; Hutter, Marcus (2022). "Formal Algorithms for Transformers". arXiv:2207.09238 [cs.LG].
- Ferrando, Javier; Sarti, Gabriele; Bisazza, Arianna; Costa-jussà, Marta R. (2024-05-01). "A Primer on the Inner Workings of Transformer-based Language Models". arXiv:2405.00208 [cs.CL].
- Leech, Gavin (2024-11-06... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#0 | Llama (language model)
Llama (Large Language Model Meta AI, formerly stylized as LLaMA) is a family of large language models (LLMs) released by Meta AI starting in February 2023.[2] The latest version is Llama 4, released in April 2025.[3]
Llama models come in different sizes, ranging from 1 billion to 2 trillion param... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#1 | ndation models.[5]
Model weights for the first version of Llama were only available to researchers on a case-by-case basis, under a non-commercial license.[6][7] Unauthorized copies of the first model were shared via BitTorrent.[8] Subsequent versions of Llama were made accessible outside academia and released under li... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#2 | ok and WhatsApp in select regions, and a standalone website. Both services use a Llama 3 model.[10]
Background
[edit]After the release of large language models such as GPT-3, a focus of research was up-scaling models which in some instances showed major increases in emergent capabilities.[11] The release of ChatGPT and... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#3 | 's Chief AI scientist Yann LeCun stated that large language models are best for aiding with writing.[13][14][15][16]
An empirical investigation of the Llama series was the scaling laws. It was observed that the Llama 3 models showed that when a model is trained on data that is more than the "Chinchilla-optimal" amount,... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#4 | , but performance continued to scale log-linearly to the 75-times larger dataset of 15 trillion tokens.[17]
Initial release
[edit]LLaMA was announced on February 24, 2023, via a blog post and a paper describing the model's training, architecture, and performance.[18][7] The inference code used to run the model was publ... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#5 | ccess to be granted "on a case-by-case basis to academic researchers; those affiliated with organizations in government, civil society, and academia; and industry research laboratories around the world".[7]
Llama was trained on only publicly available information, and was trained at various model sizes, with the intent... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#6 | d examples of instruction fine-tuned versions of the model.[18]
Meta AI reported the 13B parameter model performance on most NLP benchmarks exceeded that of the much larger GPT-3 (with 175B parameters), and the largest 65B model was competitive with state of the art models such as PaLM and Chinchilla.[18]
Leak
[edit]On... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#7 | ubsequently spread through online AI communities.[20] That same day, a pull request on the main LLaMA repository was opened, requesting to add the magnet link to the official documentation.[21][22] On March 4, a pull request was opened to add links to HuggingFace repositories containing the model.[23][21] On March 6, M... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#8 | distribution" of the model. HuggingFace complied with the requests.[24] On March 20, Meta filed a DMCA takedown request for copyright infringement against a repository containing a script that downloaded LLaMA from a mirror, and GitHub complied the next day.[25]
Reactions to the leak varied. Some speculated that the mo... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#9 | as the fact that smaller versions of the model can be run relatively cheaply, suggesting that this will promote the flourishing of additional research developments.[20] Multiple commentators, such as Simon Willison, compared LLaMA to Stable Diffusion, a text-to-image model which, unlike comparably sophisticated models ... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#10 | ]
LLaMa 2
[edit]On July 18, 2023, in partnership with Microsoft, Meta announced LLaMa 2, the next generation of Llama. Meta trained and released Llama 2 in three model sizes: 7, 13, and 70 billion parameters.[5] The model architecture remains largely unchanged from that of LLaMA-1 models, but 40% more data was used to ... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#11 | in the future upon satisfying safety targets.
LLaMa 2 includes foundation models and models fine-tuned for chat. In a further departure from the original version of LLaMa, all models are released with weights and may be used for many commercial use cases. However, because LLaMa's license enforces an acceptable use poli... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#12 | by the Open Source Initiative (which maintains The Open Source Definition) and others.[28][29]
Code Llama is a fine-tune of LLaMa 2 with code specific datasets. 7B, 13B, and 34B versions were released on August 24, 2023, with the 70B releasing on the January 29, 2024.[30] Starting with the foundation models from LLaMa ... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#13 | he Code Llama foundation models. This foundation model was further trained on 5B instruction following token to create the instruct fine-tune. Another foundation model was created for Python code, which trained on 100B tokens of Python-only code, before the long-context data.[31]
Llama 3
[edit]On April 18, 2024, Meta r... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#14 | text gathered from “publicly available sources” with the instruct models fine-tuned on “publicly available instruction datasets, as well as over 10M human-annotated examples". Meta AI's testing showed in April 2024 that Llama 3 70B was beating Gemini Pro 1.5 and Claude 3 Sonnet on most benchmarks. Meta also announced p... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#15 | ing an interview with Dwarkesh Patel, Mark Zuckerberg said that the 8B version of Llama 3 was nearly as powerful as the largest Llama 2. Compared to previous models, Zuckerberg stated the team was surprised that the 70B model was still learning even at the end of the 15T tokens training. The decision was made to end tr... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#16 | 35][36]
Llama 4
[edit]The Llama-4 series was released in 2025. The architecture was changed to a mixture of experts. They are multimodal (text and image input, text output) and multilingual (12 languages).[37] Specifically, on 5 April 2025, the following were released both as base and instruction-tuned versions:[38]
- ... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#17 | lion active parameter model with 128 experts, context window of 1M, with 400B parameters in total.
Also claimed was Behemoth (not yet released): 288 billion active parameter model with 16 experts and around 2T parameters in total. The Behemoth version was still in training at that time. The Scout was trained from scrat... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#18 | Maverick.
The training data included publicly available data, licensed data, and Meta-proprietary data such as publicly shared posts from Instagram and Facebook and people’s interactions with Meta AI. The data cutoff was August 2024.[37]
Meta claimed in its release announcement that Llama 4 bested GPT-4o's score on the... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#19 | hat version" of the model that was "optimized for conversationality", which differed from the version of Llama 4 released to the public.[40] LMArena indicated that it would change its policies to prevent this incident from reoccurring, and responded, "Meta's interpretation of our policy did not match what we expect fro... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#20 | for human preference."[39] Some users criticized Meta on social media for its use of a separate model version tailored for benchmarking, and some additionally accused Meta of training Llama 4 on test sets to further boost its benchmark scores—which Meta denied.[41]
Comparison of models
[edit]For the training cost colum... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#21 | etaFLOP-day. Also, 1 petaFLOP-day = 1 petaFLOP/sec × 1 day = 8.64E19 FLOP. "T" means "trillion" and "B" means "billion".
The following table lists the main model versions of Llama, describing the significant changes included with each version:[42]
Architecture and training
[edit]Here is the recommendation letter that I... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#22 | ears, and I believe that she would be an excellent dragon feeder for the Magic Unicorn Corporation. ___ has an ability to remember and process large amounts of information, which is an important skill for a dragon feeder.
___, as an accomplished knight, has a deep understanding of how to kill dragons and how to use eac... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#23 | erous to each dragon. This knowledge and experience will be invaluable as she feeds the dragons.
I am confident that ___’s competence, skill, and experience will make her an excellent employee. Please contact me at (___) ___-___ if you have any questions. I look forward to hearing from you.
Best regards,
Honorable Knig... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#24 | e some minor differences:
- SwiGLU[51] activation function instead of GeLU;
- rotary positional embeddings (RoPE)[52] instead of absolute positional embedding;
- RMSNorm[53] instead of layer normalization;[54]
Training datasets
[edit]LLaMA's developers focused their effort on scaling the model's performance by increasi... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#25 | ference on the trained model rather than the computational cost of the training process.
LLaMA 1 foundational models were trained on a data set with 1.4 trillion tokens, drawn from publicly available data sources, including:[18]
- Webpages scraped by CommonCrawl
- Open source repositories of source code from GitHub
- W... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#26 | c papers uploaded to ArXiv
- Questions and answers from Stack Exchange websites
On April 17, 2023, TogetherAI launched a project named RedPajama to reproduce and distribute an open source version of the LLaMA dataset.[55] The dataset has approximately 1.2 trillion tokens and is publicly available for download.[56]
Llam... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#27 | n disclose personal data of people. It also upsamples sources considered trustworthy.[27] Llama 2 - Chat was additionally fine-tuned on 27,540 prompt-response pairs created for this project, which performed better than larger but lower-quality third-party datasets. For AI alignment, reinforcement learning with human fe... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#28 | in the Meta examples, 3.0 for Anthropic Helpful and Anthropic Harmless sets, and 1.0 for five other sets, including OpenAI Summarize, StackExchange, etc.
Llama 3 consists of mainly English data, with over 5% in over 30 other languages. Its dataset was filtered by a text-quality classifier, and the classifier was traine... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#29 | g was alleged to have authorized the use of copyrighted content from Library Genesis to train Llama AI models and conceal its actions by removing copyright markers from the data.[57]
Fine-tuning
[edit]Llama 1 models are only available as foundational models with self-supervised learning and without fine-tuning. Llama 2... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#30 | a 2 and Code Llama - Chat have the same context length of 4K tokens. Supervised fine-tuning used an autoregressive loss function with token loss on user prompts zeroed out. The batch size was 64.
For AI alignment, human annotators wrote prompts and then compared two model outputs (a binary protocol), giving confidence ... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#31 | elpfulness using Reinforcement learning from human feedback (RLHF). A major technical contribution is the departure from the exclusive use of Proximal Policy Optimization (PPO) for RLHF – a new technique based on Rejection sampling was used, followed by PPO.
Multi-turn consistency in dialogs was targeted for improvemen... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#32 | ing the dialog. This was accomplished using the new "Ghost attention" technique during training, which concatenates relevant instructions to each new user message but zeros out the loss function for tokens in the prompt (earlier parts of the dialog).
Applications
[edit]The Stanford University Institute for Human-Center... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#33 | LaMA 7B model that uses the "Self-Instruct" method of instruction tuning to acquire capabilities comparable to the OpenAI GPT-3 series text-davinci-003 model at a modest cost.[58][59][60] The model files were officially removed on March 21, 2023, over hosting costs and safety concerns, though the code and paper remain ... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#34 | and articles. It was created by researchers at École Polytechnique Fédérale de Lausanne School of Computer and Communication Sciences, and the Yale School of Medicine. It shows increased performance on medical-related benchmarks such as MedQA and MedMCQA.[64][65][66]
Zoom used Meta Llama 2 to create an AI Companion tha... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#35 | ultiple models, including Meta Llama 2.[67]
Reuters reported in 2024 that many Chinese foundation models relied on Llama models for their training.[68]
llama.cpp
[edit]Software developer Georgi Gerganov released llama.cpp as open-source on March 10, 2023. It's a re-implementation of LLaMA in C++, allowing systems witho... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#36 | both tensors and metadata.[70] The format focuses on supporting different quantization types, which can reduce memory usage, and increase speed at the expense of lower model precision.[71]
llamafile created by Justine Tunney is an open-source tool that bundles llama.cpp with the model into a single executable file. Tun... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#37 | or FP16 and 8-bit quantized data types.[72]
Military
[edit]In 2024, researchers from the People's Liberation Army Academy of Military Sciences (top military academy of China) were reported to have developed a military tool using Llama, which Meta Platforms stated was unauthorized due to Llama's license prohibiting the ... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#38 | in November 2024, but continued to prohibit military use by non-US entities.[29][75]
Reception
[edit]Wired describes the 8B parameter version of Llama 3 as being "surprisingly capable" given its size.[76]
The response to Meta's integration of Llama into Facebook was mixed, with some users confused after Meta AI told a ... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#39 | o improve on model safety, iteration speed, increase adoption among developers and researchers, and to become the industry standard. Llama 5, 6, and 7 are planned for the future.[78]
The release of Llama models has sparked significant debates on the benefits and misuse risks of open weight models. Such models can be fi... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#40 | re models may facilitate causing damage more than defending against it, for example by making it relatively easy to engineer advanced bioweapons without specialized knowledge. Conversely, open-weight models can be useful for a wide variety of purposes, including for safety research.[79]
Open Source Initiative head Stef... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#41 | the term.[80]
See also
[edit]- GPT-4o
- IBM Granite, an open-source LLM made by IBM
- Mistral AI, a French open-source AI company
References
[edit]- ^ "llama-models/models/llama3_2/LICENSE at main · meta-llama/llama-models · GitHub". GitHub. Archived from the original on 2024-09-29. Retrieved 2024-10-20.
- ^ Leswing, K... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#42 | ^ Franzen, Carl (2025-04-08). "Meta defends Llama 4 release against 'reports of mixed quality,' blames bugs". VentureBeat. Retrieved 2025-04-10.
- ^ a b Peters, Jay; Vincent, James (24 February 2023). "Meta has a new machine learning language model to remind you it does AI too". The Verge.
- ^ a b c "Meta and Microsoft... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#43 | 2023.
- ^ Malik, Yuvraj; Paul, Katie (25 February 2023). "Meta heats up Big Tech's AI arms race with new language model". Reuters.
- ^ a b c "Introducing LLaMA: A foundational, 65-billion-parameter large language model". Meta AI. 24 February 2023. Archived from the original on 3 March 2023. Retrieved 16 March 2023.
- ^... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#44 | Retrieved 2025-04-10.
- ^ David, Emilia (30 October 2023). "Meta's AI research head wants open source licensing to change". The Verge. Archived from the original on 14 September 2024. Retrieved 20 October 2024.
- ^ Heath, Alex (2024-04-18). "Meta's battle with ChatGPT begins now". The Verge. Retrieved 2025-04-10.
- ^ "... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#45 | was built from the people who made it". MIT Technology Review. Archived from the original on 2023-03-03. Retrieved 2024-10-20.
- ^ Ray, Tiernan (23 January 2023). "ChatGPT is 'not particularly innovative,' and 'nothing revolutionary', says Meta's chief AI scientist". ZDNET. Archived from the original on 2023-02-17.
- ^... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#46 | om the original on 22 July 2024. Retrieved 20 October 2024.
- ^ "Yann LeCun on LinkedIn: My unwavering opinion on current (auto-regressive) LLMs". LinkedIn. Archived from the original on 2024-09-17. Retrieved 2024-10-20.
- ^ "Meta's Yann LeCun Asks How AIs will Match — and Exceed — Human-level Intelligence". 23 October... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#47 | from the original on 2024-05-15. Retrieved 2024-04-21.
- ^ a b c d e Touvron, Hugo; Lavril, Thibaut; Izacard, Gautier; Martinet, Xavier; Lachaux, Marie-Anne; Lacroix, Timothée; Rozière, Baptiste; Goyal, Naman; Hambro, Eric; Azhar, Faisal; Rodriguez, Aurelien; Joulin, Armand; Grave, Edouard; Lample, Guillaume (2023). "L... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#48 | 15 March 2023. Retrieved 16 March 2023.
- ^ a b c Vincent, James (8 March 2023). "Meta's powerful AI language model has leaked online — what happens now?". The Verge. Archived from the original on 3 November 2023. Retrieved 16 March 2023.
- ^ a b VK, Anirudh (6 March 2023). "Meta's LLaMA Leaked to the Public, Thanks To... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#49 | sing a torrent to distribute more efficiently by ChristopherKing42 · Pull Request #73 · facebookresearch/llama". GitHub. Archived from the original on 10 April 2023. Retrieved 25 March 2023.
- ^ "Download weights from hugging face to help us save bandwidth by Jainam213 · Pull Request #109 · facebookresearch/llama". Git... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#50 | rge Language Model Leaks Online". Vice. Archived from the original on 6 April 2023. Retrieved 17 March 2023.
- ^ OpSec Online LLC (21 March 2023). "github/dmca - Notice of Claimed Infringement via Email". GitHub. Archived from the original on 10 April 2023. Retrieved 25 March 2023.
- ^ Willison, Simon (11 March 2023). ... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#51 | 2023. Retrieved 16 March 2023.
- ^ a b c Touvron, Hugo; Martin, Louis; et al. (18 Jul 2023). "LLaMA-2: Open Foundation and Fine-Tuned Chat Models". arXiv:2307.09288 [cs.CL].
- ^ Edwards, Benj (2023-07-18). "Meta launches LLaMA-2, a source-available AI model that allows commercial applications [Updated]". Ars Technica. ... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#52 | AI to US government for national security". CIO. Retrieved 9 December 2024.
- ^ "Introducing Code Llama, a state-of-the-art large language model for coding". ai.meta.com. Archived from the original on 2024-09-27. Retrieved 2024-10-20.
- ^ Rozière, Baptiste; Gehring, Jonas; Gloeckle, Fabian; Sootla, Sten; Gat, Itai; Tan... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#53 | 308.12950 [cs.CL].
- ^ Wiggers, Kyle (18 April 2024). "Meta releases Llama 3, claims it's among the best open models available". TechCrunch. Archived from the original on 18 September 2024. Retrieved 20 October 2024.
- ^ Mann, Tobias (April 19, 2024). "Meta debuts third-generation Llama large language model". The Regis... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#54 | - Llama 3, Open Sourcing $10b Models, & Caesar Augustus". www.dwarkeshpatel.com. Archived from the original on 2024-07-16. Retrieved 2024-08-01.
the 8 billion is nearly as powerful as the biggest version of Llama 2 that we released [...] even by the end, it was... still learning right it's like we probably could have f... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#55 | do these meta reasoning questions of [...] how do I want to spend our GPUs
- ^ "Introducing Llama 3.1: Our most capable models to date". ai.meta.com. July 23, 2024. Archived from the original on 2024-07-23. Retrieved 2024-07-23.
- ^ a b Dubey, Abhimanyu; Jauhri, Abhinav; Pandey, Abhinav; Kadian, Abhishek; Al-Dahle, Ahm... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#56 | "meta-llama/Llama-4-Maverick-17B-128E · Hugging Face". huggingface.co. 2025-04-05. Retrieved 2025-04-06.
- ^ "The Llama 4 herd: The beginning of a new era of natively multimodal AI innovation". ai.meta.com. Archived from the original on 2025-04-05. Retrieved 2025-04-05.
- ^ a b Robison, Kylie (8 April 2025). "Meta got ... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#57 | AI models are a bit misleading". TechCrunch. Retrieved 8 April 2025.
- ^ Franzen, Carl (8 April 2025). "Meta defends Llama 4 release against 'reports of mixed quality,' blames bugs". VentureBeat. Retrieved 8 April 2025.
- ^ "Llama Models". www.llama.com. Archived from the original on April 9, 2025. Retrieved April 20, ... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#58 | ved 2023-06-20.
- ^ "llama/MODEL_CARD.md at main · meta-llama/llama". GitHub. Archived from the original on 2024-05-28. Retrieved 2024-05-28.
- ^ "Andrej Karpathy (Apr 18, 2024), The model card has some more interesting info too". X (formerly Twitter). Archived from the original on August 17, 2024. Retrieved October 20... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#59 | 5-28.
- ^ "llama-models/models/llama3_1/MODEL_CARD.md at main · meta-llama/llama-models". GitHub. Archived from the original on 2024-07-23. Retrieved 2024-07-23.
- ^ Robison, Kylie (2024-09-25). "Meta releases its first open AI model that can process images". The Verge. Retrieved 2024-09-25.
- ^ Wiggers, Kyle (2024-09-... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#60 | ma 3.2: Revolutionizing edge AI and vision with open, customizable models". ai.meta.com. Archived from the original on 2024-09-25. Retrieved 2024-09-26.
- ^ Shazeer, Noam (2020-02-01). "GLU Variants Improve Transformer". arXiv:2002.05202 [cs.CL].
- ^ Su, Jianlin; Lu, Yu; Pan, Shengfeng; Murtadha, Ahmed; Wen, Bo; Liu, Y... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#61 | ennrich, Rico (2019-10-01). "Root Mean Square Layer Normalization". arXiv:1910.07467 [cs.LG].
- ^ Lei Ba, Jimmy; Kiros, Jamie Ryan; Hinton, Geoffrey E. (2016-07-01). "Layer Normalization". arXiv:1607.06450 [stat.ML].
- ^ "RedPajama-Data: An Open Source Recipe to Reproduce LLaMA training dataset". GitHub. Together. Arch... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#62 | e original on 3 November 2023. Retrieved 4 May 2023.
- ^ Wiggers, Kyle (January 9, 2025). "Mark Zuckerberg gave Meta's Llama team the OK to train on copyrighted works, filing claims". Techcrunch. Retrieved January 12, 2025.
- ^ Taori, Rohan; Gulrajani, Ishaan; Zhang, Tianyi; Dubois, Yann; Li, Xuechen; Guestrin, Carlos;... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#63 | r for Research on Foundation Models. Archived from the original on 6 April 2023.
- ^ Wang, Yizhong; Kordi, Yeganeh; Mishra, Swaroop; Liu, Alisa; Smith, Noah A.; Khashabi, Daniel; Hajishirzi, Hannaneh (2022). "Self-Instruct: Aligning Language Models with Self-Generated Instructions". arXiv:2212.10560 [cs.CL].
- ^ "Stanf... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#64 | costly, risky Alpaca AI model offline". www.theregister.com.
- ^ "Stanford Researchers Take Down Alpaca AI Over Cost and Hallucinations". Gizmodo. 21 March 2023. Archived from the original on 12 May 2024. Retrieved 20 October 2024.
- ^ "alpaca-lora". GitHub. Archived from the original on 4 April 2023. Retrieved 5 April... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#65 | November 2023). "EPFL's new Large Language Model for Medical Knowledge". Archived from the original on 17 September 2024. Retrieved 20 October 2024.
- ^ "epfLLM/meditron". epfLLM. 11 May 2024. Archived from the original on 27 September 2024. Retrieved 20 October 2024.
- ^ "How Companies Are Using Meta Llama". Meta. 7 M... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#66 | intelligence technology?". Reuters. May 9, 2024.
- ^ Edwards, Benj (2023-03-13). "You can now run a GPT-3-level AI model on your laptop, phone, and Raspberry Pi". Ars Technica. Archived from the original on 2024-01-09. Retrieved 2024-01-04.
- ^ "GGUF". huggingface.co. Retrieved 9 May 2024.
- ^ Labonne, Maxime (29 Novem... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#67 | 4. Retrieved 9 May 2024.
- ^ Connatser, Matthew. "Llamafile LLM driver project boosts performance on CPU cores". www.theregister.com. Archived from the original on 10 May 2024. Retrieved 10 May 2024.
- ^ Cheung, Sunny (October 31, 2024). "PRC Adapts Meta's Llama for Military and Security AI Applications". Jamestown Fou... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#68 | tary use on back of Meta's Llama". Reuters. Retrieved November 1, 2024.
- ^ Smith, Matthew S. (17 November 2024). "Meta Opens Its AI Model for the U.S. Military - IEEE Spectrum". IEEE Spectrum. Retrieved 9 December 2024.
- ^ Knight, Will. "Meta's Open Source Llama 3 Is Already Nipping at OpenAI's Heels". Wired. Archive... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#69 | ril 2024. Archived from the original on 2024-09-17. Retrieved 2024-10-20.
- ^ "Archived copy" (PDF). Archived (PDF) from the original on 2024-09-17. Retrieved 2024-10-20.
{{cite web}}
: CS1 maint: archived copy as title (link) - ^ Knight, Will. "Meta's New Llama 3.1 AI Model Is Free, Powerful, and Risky". Wired. ISSN 1... |
https://en.wikipedia.org/wiki/Llama_%28language_model%29#70 | for 'polluting' open-source". Financial Times.
Further reading
[edit]- Huang, Kalley; O'Regan, Sylvia Varnham (September 5, 2023). "Inside Meta's AI Drama: Internal Feuds Over Compute Power". The Information. Archived from the original on September 5, 2023. Retrieved September 6, 2023. |
https://en.wikipedia.org/wiki/T5_%28language_model%29#0 | T5 (language model)
T5 (Text-to-Text Transfer Transformer) is a series of large language models developed by Google AI introduced in 2019.[1][2] Like the original Transformer model,[3] T5 models are encoder-decoder Transformers, where the encoder processes the input text, and the decoder generates the output text.
T5 m... |
https://en.wikipedia.org/wiki/T5_%28language_model%29#1 | ilar to their pretrained tasks. They can also be finetuned to perform other tasks.
T5 models have been employed in various applications, including chatbots, machine translation systems, text summarization tools, code generation, and robotics.[4]
Training
[edit]The original T5 models are pre-trained on the Colossal Clea... |
https://en.wikipedia.org/wiki/T5_%28language_model%29#2 | eneral language understanding and generation abilities. T5 models can then be fine-tuned on specific downstream tasks, adapting their knowledge to perform well in various applications.
The T5 models were pretrained on many tasks, all in the format of <input text>
-> <output text>
.
Some examples are:
- restoring corrup... |
https://en.wikipedia.org/wiki/T5_%28language_model%29#3 | >
and<Y>
denote blanks to be filled, called "sentinels" in the original report. - translation:
translate English to German: That is good.
->Das ist gut.
. - judging the grammatical acceptability of a sentence (CoLA sentence):
The course is jumping well.
->not acceptable
.
Architecture
[edit]The T5 series encompasses se... |
https://en.wikipedia.org/wiki/T5_%28language_model%29#4 | d the decoder generates the output text.
These models are often distinguished by their parameter count, which indicates the complexity and potential capacity of the model. The original paper[1] reported the following 5 models:
*The encoder and the decoder have the same shape. So for example, the T5-small has 6 layers i... |
https://en.wikipedia.org/wiki/T5_%28language_model%29#5 | decoder. They always have the same number of layers.
- : Number of attention heads in each attention block.
- : Dimension of the embedding vectors.
- : Dimension of the feedforward network within each encoder and decoder layer.
- : Dimension of the key and value vectors used in the self-attention mechanism.
Note that u... |
https://en.wikipedia.org/wiki/T5_%28language_model%29#6 | difications: layer normalization with no additive bias; placing the layer normalization outside the residual path; relative positional embedding.[7]
For all experiments, they used a WordPiece tokenizer, with vocabulary size 32,000. The tokenizer is shared across both the input and output of each model. It was trained o... |
https://en.wikipedia.org/wiki/T5_%28language_model%29#7 | equent models used the T5 architecture, with non-standardized naming conventions used to differentiate them. This section attempts to collect the main ones. An exhaustive list of the variants released by Google Brain is on the GitHub repo for T5X.[8]
Some models are trained from scratch while others are trained by star... |
https://en.wikipedia.org/wiki/T5_%28language_model%29#8 | e, 3B, 11B (2019): The original models.[1]
- T5 1.1 small, base, large, XL, XXL: Improved versions of the original T5 series. These have roughly equal parameters. The activation function is GEGLU[9] instead of ReLU. The 3B and the 11B were changed to "XL" and "XXL", and their shapes are changed:[8][10][11]
- LM-adapted... |
https://en.wikipedia.org/wiki/T5_%28language_model%29#9 | itional tokens from C4.[12]
- Switch Transformer (2021): a mixture-of-experts variant of T5, by replacing the feedforward layers in the encoder and decoder blocks with mixture of expert feedforward layers.[13][14]
- T0 3B, 11B (2021): a series of models that started from checkpoints of LM-adapted T5, and further traine... |
https://en.wikipedia.org/wiki/T5_%28language_model%29#10 | [16]
- ByT5 (2021): a byte-level version of T5, trained on mC4 (multilingual C4) dataset.[17] It operates on text encoded as UTF-8 bytes, without tokenizers.
- Flan-T5-XL (2022): a model that started with a checkpoint of T5 XL, then instruction-tuned on the FLAN dataset.[18][19][20][21]
- T5X (2022): a JAX-based re-imp... |
https://en.wikipedia.org/wiki/T5_%28language_model%29#11 | .[2]
- UL2 20B (2022): a model with the same architecture as the T5 series, but scaled up to 20B, and trained with "mixture of denoisers" objective on the C4.[23] It was trained on a TPU cluster by accident, when a training run was left running accidentally for a month.[24]
- Flan-UL2 20B (2022): UL2 20B instruction-fi... |
https://en.wikipedia.org/wiki/T5_%28language_model%29#12 | trained on The Pile. It came in sizes of base, large, XL, XXL.[25]
Applications
[edit]The T5 model itself is an encoder-decoder model, allowing it to be used for instruction following. The encoder encodes the instruction, and the decoder autoregressively generates the reply.
The T5 encoder can be used as a text encoder... |
https://en.wikipedia.org/wiki/T5_%28language_model%29#13 | ample, Google Imagen[26] uses T5-XXL as text encoder, and the encoded text vectors are used as conditioning on a diffusion model. As another example, the AuraFlow diffusion model[27] uses Pile-T5-XL.
References
[edit]- ^ a b c Raffel, Colin; Shazeer, Noam; Roberts, Adam; Lee, Katherine; Narang, Sharan; Matena, Michael;... |
https://en.wikipedia.org/wiki/T5_%28language_model%29#14 | Journal of Machine Learning Research. 21 (140): 1–67. arXiv:1910.10683. ISSN 1533-7928.
- ^ a b google-research/text-to-text-transfer-transformer, Google Research, 2024-08-21, retrieved 2024-08-21
- ^ Vaswani, Ashish; Shazeer, Noam; Parmar, Niki; Uszkoreit, Jakob; Jones, Llion; Gomez, Aidan N; Kaiser, Łukasz; Polosukhi... |
https://en.wikipedia.org/wiki/T5_%28language_model%29#15 | iang, Yunfan; Gupta, Agrim; Zhang, Zichen; Wang, Guanzhi; Dou, Yongqiang; Chen, Yanjun; Fei-Fei, Li; Anandkumar, Anima; Zhu, Yuke (2022-10-06). "VIMA: General Robot Manipulation with Multimodal Prompts". arXiv:2210.03094 [cs.RO].
- ^ a b Zhang, Aston; Lipton, Zachary; Li, Mu; Smola, Alexander J. (2024). "11.9. Large-Sc... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.