Audience
LLM and AI developers
About OpenLLaMA
OpenLLaMA is a permissively licensed open source reproduction of Meta AI’s LLaMA 7B trained on the RedPajama dataset. Our model weights can serve as the drop in replacement of LLaMA 7B in existing implementations. We also provide a smaller 3B variant of LLaMA model.
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PygmalionAI is a community dedicated to creating open-source projects based on EleutherAI's GPT-J 6B and Meta's LLaMA models. In simple terms, Pygmalion makes AI fine-tuned for chatting and roleplaying purposes. The current actively supported Pygmalion AI model is the 7B variant, based on Meta AI's LLaMA model. With only 18GB (or less) VRAM required, Pygmalion offers better chat capability than much larger language models with relatively minimal resources. Our curated dataset of high-quality roleplaying data ensures that your bot will be the optimal RP partner. Both the model weights and the code used to train it are completely open-source, and you can modify/re-distribute it for whatever purpose you want. Language models, including Pygmalion, generally run on GPUs since they need access to fast memory and massive processing power in order to output coherent text at an acceptable speed.
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Llama 2
The next generation of our open source large language model. This release includes model weights and starting code for pretrained and fine-tuned Llama language models — ranging from 7B to 70B parameters.
Llama 2 pretrained models are trained on 2 trillion tokens, and have double the context length than Llama 1. Its fine-tuned models have been trained on over 1 million human annotations.
Llama 2 outperforms other open source language models on many external benchmarks, including reasoning, coding, proficiency, and knowledge tests.
Llama 2 was pretrained on publicly available online data sources. The fine-tuned model, Llama-2-chat, leverages publicly available instruction datasets and over 1 million human annotations.
We have a broad range of supporters around the world who believe in our open approach to today’s AI — companies that have given early feedback and are excited to build with Llama 2.
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RedPajama
Foundation models such as GPT-4 have driven rapid improvement in AI. However, the most powerful models are closed commercial models or only partially open. RedPajama is a project to create a set of leading, fully open-source models. Today, we are excited to announce the completion of the first step of this project: the reproduction of the LLaMA training dataset of over 1.2 trillion tokens.
The most capable foundation models today are closed behind commercial APIs, which limits research, customization, and their use with sensitive data. Fully open-source models hold the promise of removing these limitations, if the open community can close the quality gap between open and closed models. Recently, there has been much progress along this front. In many ways, AI is having its Linux moment. Stable Diffusion showed that open-source can not only rival the quality of commercial offerings like DALL-E but can also lead to incredible creativity from broad participation by communities.
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Falcon-40B
Falcon-40B is a 40B parameters causal decoder-only model built by TII and trained on 1,000B tokens of RefinedWeb enhanced with curated corpora. It is made available under the Apache 2.0 license.
Why use Falcon-40B?
It is the best open-source model currently available. Falcon-40B outperforms LLaMA, StableLM, RedPajama, MPT, etc. See the OpenLLM Leaderboard.
It features an architecture optimized for inference, with FlashAttention and multiquery.
It is made available under a permissive Apache 2.0 license allowing for commercial use, without any royalties or restrictions.
⚠️ This is a raw, pretrained model, which should be further finetuned for most usecases. If you are looking for a version better suited to taking generic instructions in a chat format, we recommend taking a look at Falcon-40B-Instruct.
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Pricing
Starting Price:
Free
Pricing Details:
Open source
Free Version:
Free Version available.
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No integrations listed.
Company Information
OpenLLaMA
Founded: 2023
github.com/openlm-research/open_llama
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