Find and compare the best Artificial Intelligence software for GaiaNet in 2024
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Use the comparison tool below to compare the top Artificial Intelligence software for GaiaNet on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.
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OpenAI's mission, which is to ensure artificial general intelligence (AGI), benefits all people. This refers to highly autonomous systems that outperform humans in most economically valuable work. While we will try to build safe and useful AGI, we will also consider our mission accomplished if others are able to do the same. Our API can be used to perform any language task, including summarization, sentiment analysis and content generation. You can specify your task in English or use a few examples. Our constantly improving AI technology is available to you with a simple integration. These sample completions will show you how to integrate with the API.
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Snyk
Snyk
$0Snyk is the leader in developer security. We empower the world’s developers to build secure applications and equip security teams to meet the demands of the digital world. Our developer-first approach ensures organizations can secure all of the critical components of their applications from code to cloud, leading to increased developer productivity, revenue growth, customer satisfaction, cost savings and an overall improved security posture. Snyk is a developer security platform that automatically integrates with a developer’s workflow and is purpose-built for security teams to collaborate with their development teams. -
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Qwen-7B
Alibaba
FreeQwen-7B, also known as Qwen-7B, is the 7B-parameter variant of the large language models series Qwen. Tongyi Qianwen, proposed by Alibaba Cloud. Qwen-7B, a Transformer-based language model, is pretrained using a large volume data, such as web texts, books, code, etc. Qwen-7B is also used to train Qwen-7B Chat, an AI assistant that uses large models and alignment techniques. The Qwen-7B features include: Pre-trained with high quality data. We have pretrained Qwen-7B using a large-scale, high-quality dataset that we constructed ourselves. The dataset contains over 2.2 trillion tokens. The dataset contains plain texts and codes and covers a wide range domains including general domain data as well as professional domain data. Strong performance. We outperform our competitors in a series benchmark datasets that evaluate natural language understanding, mathematics and coding. And more. -
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Mixtral 8x7B
Mistral AI
FreeMixtral 8x7B has open weights and is a high quality sparse mixture expert model (SMoE). Licensed under Apache 2.0. Mixtral outperforms Llama 70B in most benchmarks, with 6x faster Inference. It is the strongest model with an open-weight license and the best overall model in terms of cost/performance tradeoffs. It matches or exceeds GPT-3.5 in most standard benchmarks. -
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Codestral
Mistral AI
FreeWe are proud to introduce Codestral, the first code model we have ever created. Codestral is a generative AI model that is open-weight and specifically designed for code generation. It allows developers to interact and write code using a shared API endpoint for instructions and completion. It can be used for advanced AI applications by software developers as it is able to master both code and English. Codestral has been trained on a large dataset of 80+ languages, including some of the most popular, such as Python and Java. It also includes C, C++ JavaScript, Bash, C, C++. It also performs well with more specific ones, such as Swift and Fortran. Codestral's broad language base allows it to assist developers in a variety of coding environments and projects. -
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Llama 2
Meta
FreeThe next generation of the large language model. This release includes modelweights and starting code to pretrained and fine tuned Llama languages models, ranging from 7B-70B parameters. Llama 1 models have a context length of 2 trillion tokens. Llama 2 models have a context length double that of Llama 1. The fine-tuned Llama 2 models have been trained using over 1,000,000 human annotations. Llama 2, a new open-source language model, outperforms many other open-source language models in external benchmarks. These include tests of reasoning, coding and proficiency, as well as knowledge tests. Llama 2 has been pre-trained using publicly available online data sources. Llama-2 chat, a fine-tuned version of the model, is based on publicly available instruction datasets, and more than 1 million human annotations. We have a wide range of supporters in the world who are committed to our open approach for today's AI. These companies have provided early feedback and have expressed excitement to build with Llama 2 -
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Mistral 7B
Mistral AI
We solve the most difficult problems to make AI models efficient, helpful and reliable. We are the pioneers of open models. We give them to our users, and empower them to share their ideas. Mistral-7B is a powerful, small model that can be adapted to many different use-cases. Mistral 7B outperforms Llama 13B in all benchmarks. It has 8k sequence length, natural coding capabilities, and is faster than Llama 2. It is released under Apache 2.0 License and we made it simple to deploy on any cloud. -
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Gemma
Google
Gemma is the family of lightweight open models that are built using the same research and technology as the Gemini models. Gemma was developed by Google DeepMind, along with other teams within Google. The name is derived from the Latin gemma meaning "precious stones". We're also releasing new tools to encourage developer innovation, encourage collaboration, and guide responsible use of Gemma model. Gemma models are based on the same infrastructure and technical components as Gemini, Google's largest and most powerful AI model. Gemma 2B, 7B and other open models can achieve the best performance possible for their size. Gemma models can run directly on a desktop or laptop computer for developers. Gemma is able to surpass much larger models in key benchmarks, while adhering our rigorous standards of safe and responsible outputs. -
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CodeGemma
Google
CodeGemma consists of powerful lightweight models that are capable of performing a variety coding tasks, including fill-in the middle code completion, code creation, natural language understanding and mathematical reasoning. CodeGemma offers 3 variants: a 7B model that is pre-trained to perform code completion, code generation, and natural language-to code chat. A 7B model that is instruction-tuned for instruction following and natural language-to code chat. You can complete lines, functions, or even entire blocks of code whether you are working locally or with Google Cloud resources. CodeGemma models are trained on 500 billion tokens primarily of English language data taken from web documents, mathematics and code. They generate code that is not only syntactically accurate but also semantically meaningful. This reduces errors and debugging times.
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