Find and compare the best On-Premise Artificial Intelligence software in 2024
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Use the comparison tool below to compare the top On-Premise Artificial Intelligence software on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.
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1
GPT-J
EleutherAI
FreeGPT-J, a cutting edge language model developed by EleutherAI, is a leading-edge language model. GPT-J's performance is comparable to OpenAI's GPT-3 model on a variety of zero-shot tasks. GPT-J, in particular, has shown that it can surpass GPT-3 at tasks relating to code generation. The latest version of this language model is GPT-J-6B and is built on a linguistic data set called The Pile. This dataset is publically available and contains 825 gibibytes worth of language data organized into 22 subsets. GPT-J has some similarities with ChatGPT. However, GPTJ is not intended to be a chatbot. Its primary function is to predict texts. Databricks made a major development in March 2023 when they introduced Dolly, an Apache-licensed model that follows instructions. -
2
Pythia
EleutherAI
FreePythia combines interpretationability analysis and scaling law to understand how knowledge evolves and develops during training with autoregressive transformators. -
3
Auto-GPT
Auto-GPT
FreeOpen-source experiment to make GPT-4 fully autonomous. Auto-GPT, an open-source experimental application, showcases the capabilities of GPT-4's language model. This program, powered by GPT-4 combines LLM "thoughts" to achieve any goal you specify. Auto-GPT is one of the first examples where GPT-4 runs fully autonomously. It pushes the limits of what AI can do. Internet access for searching and information gathering Memory management: Long-term and Short-term Text generation using GPT-4 Access to popular websites, platforms and apps GPT-3.5: File storage and summary with GPT Extensibility of Plugins -
4
BabyAGI
BabyAGI
FreeThis Python script is an AI-powered task manager. The system uses OpenAI, Chroma, and Chroma to create tasks, prioritize them, and execute them. This system creates tasks by analyzing the results of previous tasks, and a predefined goal. The script uses OpenAI's Natural Language Processing (NLP), and Chroma, to store and retrieve the task results in context. This is a simplified version of the original Task Driven Autonomous Agent. The script runs an infinite loop which performs the following steps. 1. The first task is selected from the list. 2. Sends the task to an execution agent. The agent uses OpenAI's OpenAI API to complete the tasks based on context. 3. Chroma enriches and stores the result. 4. Creates new tasks, and reprioritizes task list according to the result and objective of the previous task. -
5
Databerry
Databerry
$25 per monthOur platform allows you to create a custom AI bot trained on your data within seconds. Streamline your customer service, onboard new members of your team, and much more! Your AI chatbot will answer frequently asked questions, and can handle simple support requests. This allows your team to focus more on providing personalized assistance to clients. Your AI chatbot will be able to handle customer inquiries 24/7, providing efficient support when your team is not available. It's easy to integrate your AI chatbot into your website - just copy and paste the code on your site. -
6
Dolly
Databricks
FreeDolly is an inexpensive LLM that demonstrates a surprising amount of the capabilities of ChatGPT. Whereas the work from the Alpaca team showed that state-of-the-art models could be coaxed into high quality instruction-following behavior, we find that even years-old open source models with much earlier architectures exhibit striking behaviors when fine tuned on a small corpus of instruction training data. Dolly uses an open source model with 6 billion parameters from EleutherAI, which is modified to include new capabilities like brainstorming and text creation that were not present in the original. -
7
mT5
Google
FreeMultilingual T5 is a massively pretrained text-totext transformer model that has been trained using a similar recipe to T5. This repo can used to reproduce the experiments described in the mT5 article. The mC4 corpus covers 101 languages. Afrikaans, Albanian, Amharic, Arabic, Armenian, Azerbaijani, Basque, Belarusian, Bengali, Bulgarian, Burmese, Catalan, Cebuano, Chichewa, Chinese, Corsican, Czech, Danish, Dutch, English, Esperanto, Estonian, Filipino, Finnish, French, Galician, Georgian, German, Greek, Gujarati, Haitian Creole, Hausa, Hawaiian, Hebrew, Hindi, Hmong, Hungarian, Icelandic, Igbo, Indonesian, Irish, Italian, Japanese, Javanese, Kannada, Kazakh, Khmer, Korean, Kurdish, Kyrgyz, Lao, Latin, Latvian, Lithuanian, Luxembourgish, Macedonian, Malagasy, Malay, Malayalam, Maltese, Maori, Marathi, Mongolian, Nepali, Norwegian, Pashto, Persian, Polish, Portuguese, Punjabi, Romanian, Russian, Samoan, Scottish Gaelic, Serbian, Shona, Sindhi, and more. -
8
Cerebras-GPT
Cerebras
FreeThe training of state-of-the art language models is extremely difficult. They require large compute budgets, complex distributed computing techniques and deep ML knowledge. Few organizations are able to train large language models from scratch. The number of organizations that do not open source their results is increasing, even though they have the expertise and resources to do so. We at Cerebras believe in open access to the latest models. Cerebras is proud to announce that Cerebras GPT, a family GPT models with 111 million to thirteen billion parameters, has been released to the open-source community. These models are trained using the Chinchilla Formula and provide the highest accuracy within a given computing budget. Cerebras GPT has faster training times and lower training costs. It also consumes less power than any other publicly available model. -
9
n8n
n8n
$20 per monthBuild complex automations up to 10x faster without battling APIs. The days of slogging through a mess of scripts is over. JavaScript is the best choice when you want flexibility, and UI for all other tasks. n8n lets you build flexible workflows that are focused on deep data integration. With a user-friendly interface and templates that can be shared, even the less technically minded members of your team can work together on them. Contrary to other tools, complexity does not limit you. You can build anything you want, without worrying about budget. Connect APIs without code to automate basic functions. You can also use vanilla Javascript to manipulate complex data. You can implement more than one trigger. You can branch and merge your workflows. You can even pause flows while you wait for external events. Custom HTTP requests allow you to easily interface with any API or service. Separate dev and production environments with different sets of authentication data to avoid breaking live workflows. -
10
Stack AI
Stack AI
$199/month AI agents that interact and answer questions with users and complete tasks using your data and APIs. AI that can answer questions, summarize and extract insights from any long document. Transfer styles and formats, as well as tags and summaries between documents and data sources. Stack AI is used by developer teams to automate customer service, process documents, qualify leads, and search libraries of data. With a single button, you can try multiple LLM architectures and prompts. Collect data, run fine-tuning tasks and build the optimal LLM to fit your product. We host your workflows in APIs, so that your users have access to AI instantly. Compare the fine-tuning services of different LLM providers. -
11
CVAT
CVAT
$33 per monthCVAT, the leading data engine for machine-learning, allows you to annotate better. Teams at all scales use and trust CVAT for data of all sizes. CVAT's intuitive, lightning-fast user interface was developed in collaboration with real-world teams that are solving real-world issues. CVAT is used by the most ambitious AI teams in the world every day, from medical to retail to autonomous cars. CVAT can handle any input data and expected results. It works well with images, videos and even 3D. Bounding boxes and polygons. Points, skeletons. Cuboids. Trajectories. Automated interactive algorithms such as intelligent scissors, histogram equality, and others will help you annotate more efficiently. Get actionable insights from metrics such as the annotator's working hours, the number of objects per hour and more. -
12
PROCESIO
PROCESIO
€2,400 per yearAutomating PROCESIO will reduce costs, save you time, and minimize risks. Revolutionize your business processes to improve agility, boost satisfaction and improve decision-making. Business teams use PROCESIO to innovate and optimize operations. PROCESIO allows teams in business operations to easily integrate tools and become automation builders. They can also automate workflows to reduce manual labor. Data is essential for executives and sales representatives to make informed decisions. Business ops teams using Procesio can assist decision-makers in real-time by orchestrating data, validating it, and enriching it. Business ops teams are the backbone of business efficiency. They are constantly innovating and finding a more efficient method to run business processes. Rapidly scale your business with cloud-native, auto-scalable infrastructure and technology. You can create your own custom actions if you don't find the information you need to design your business process. -
13
Falcon-40B
Technology Innovation Institute (TII)
FreeFalcon-40B is a 40B parameter causal decoder model, built by TII. It was trained on 1,000B tokens from RefinedWeb enhanced by curated corpora. It is available under the Apache 2.0 licence. Why use Falcon-40B Falcon-40B is the best open source model available. Falcon-40B outperforms LLaMA, StableLM, RedPajama, MPT, etc. OpenLLM Leaderboard. It has an architecture optimized for inference with FlashAttention, multiquery and multiquery. It is available under an Apache 2.0 license that allows commercial use without any restrictions or royalties. This is a raw model that should be finetuned to fit most uses. If you're looking for a model that can take generic instructions in chat format, we suggest Falcon-40B Instruct. -
14
Falcon-7B
Technology Innovation Institute (TII)
FreeFalcon-7B is a 7B parameter causal decoder model, built by TII. It was trained on 1,500B tokens from RefinedWeb enhanced by curated corpora. It is available under the Apache 2.0 licence. Why use Falcon-7B Falcon-7B? It outperforms similar open-source models, such as MPT-7B StableLM RedPajama, etc. It is a result of being trained using 1,500B tokens from RefinedWeb enhanced by curated corpora. OpenLLM Leaderboard. It has an architecture optimized for inference with FlashAttention, multiquery and multiquery. It is available under an Apache 2.0 license that allows commercial use without any restrictions or royalties. -
15
RedPajama
RedPajama
FreeGPT-4 and other foundation models have accelerated AI's development. The most powerful models, however, are closed commercial models or partially open. RedPajama aims to create a set leading, open-source models. Today, we're excited to announce that the first phase of this project is complete: the reproduction of LLaMA's training dataset of more than 1.2 trillion tokens. The most capable foundations models are currently closed behind commercial APIs. This limits research, customization and their use with sensitive information. If the open community can bridge the quality gap between closed and open models, fully open-source models could be the answer to these limitations. Recent progress has been made in this area. AI is in many ways having its Linux moment. Stable Diffusion demonstrated that open-source software can not only compete with commercial offerings such as DALL-E, but also lead to incredible creative results from community participation. -
16
Vicuna
lmsys.org
FreeVicuna-13B, an open-source chatbot, is trained by fine-tuning LLaMA using user-shared conversations from ShareGPT. Vicuna-13B's preliminary evaluation using GPT-4, as a judge, shows that it achieves a quality of more than 90%* for OpenAI ChatGPT or Google Bard and outperforms other models such as LLaMA or Stanford Alpaca. Vicuna-13B costs around $300 to train. The online demo and the code, along with weights, are available to non-commercial users. -
17
MPT-7B
MosaicML
FreeIntroducing MPT-7B - the latest addition to our MosaicML Foundation Series. MPT-7B, a transformer that is trained from scratch using 1T tokens of code and text, is the latest entry in our MosaicML Foundation Series. It is open-source, available for commercial purposes, and has the same quality as LLaMA-7B. MPT-7B trained on the MosaicML Platform in 9.5 days, with zero human interaction at a cost $200k. You can now train, fine-tune and deploy your private MPT models. You can either start from one of our checkpoints, or you can start from scratch. For inspiration, we are also releasing three finetuned models in addition to the base MPT-7B: MPT-7B-Instruct, MPT-7B-Chat, and MPT-7B-StoryWriter-65k+, the last of which uses a context length of 65k tokens! -
18
OpenLLaMA
OpenLLaMA
FreeOpenLLaMA, a permissively-licensed open source reproduction of Meta AI’s LLaMA 7B, is trained on the RedPajama data set. Our model weights are a drop-in replacement for LLaMA7B in existing implementations. We also offer a smaller 3B version of the LLaMA Model. -
19
Karlo
Kakao Brain
FreeKarlo is a model that generates images from text prompts. It builds on OpenAI's unCLIP architecture, but goes a step beyond by enhancing the super-resolution standard model, allowing for intricate details to be recovered at a remarkable 256px resolution, all while minimising noise through a small number of denoising stages. We embarked on a lengthy training process to create Karlo. We started from the beginning, using a large dataset of 115 millions image-text pairs. This included COYO100M, CC3M and CC12M. For the Prior and Decoder components we used the power of ViT/L/14, an OpenAI CLIP text encoder. We made a significant change to the unCLIP implementation in order to optimize efficiency. We integrated the text encoder of ViT-L/14 into the decoder instead of using a trainable transform. -
20
TextGears
TextGears
$4.90TextGears provides translation, paraphrasing and text checking services for hundreds companies around the globe. Free demo available online. API allows to integrate TextGears text analysis into any modern software product. On-premise installation will be the best options for those companies that cannot use any services our of the corporate network. Supported languages include: English, French, German, Portuguese, Russian, Italian, Arabic, Spanish, Japanese, Chinese and Greek. -
21
SuperAGI
SuperAGI
FreeInfrastructure to build, run, and manage autonomous agents Open-source AI framework that allows you to quickly and reliably develop and deploy useful agents. -
22
Baichuan-13B
Baichuan Intelligent Technology
FreeBaichuan-13B, a large-scale language model with 13 billion parameters that is open source and available commercially by Baichuan Intelligent, was developed following Baichuan -7B. It has the best results for a language model of the same size in authoritative Chinese and English benchmarks. This release includes two versions of pretraining (Baichuan-13B Base) and alignment (Baichuan-13B Chat). Baichuan-13B has more data and a larger size. It expands the number parameters to 13 billion based on Baichuan -7B, and trains 1.4 trillion coins on high-quality corpus. This is 40% more than LLaMA-13B. It is open source and currently the model with the most training data in 13B size. Support Chinese and English bi-lingual, use ALiBi code, context window is 4096. -
23
FreeWilly
Stability AI
FreeStability AI, in collaboration with its CarperAI Lab, is proud to announce FreeWilly1 (and its successor FreeWilly2), two powerful, new Large Language Models. Both models show exceptional reasoning abilities across a variety of benchmarks. FreeWilly1 leverages the original LLaMA 65B foundation model and was carefully fine-tuned with a new synthetically-generated dataset using Supervised Fine-Tune (SFT) in standard Alpaca format. FreeWilly2 uses the LLaMA 70B foundation model in order to achieve a performance that is comparable with GPT-3.5 on some tasks. The FreeWilly models were inspired by Microsoft's "Orca: Progressive Learning from Complex Explanation traces of GPT-4" paper. While our data generation processes are similar, our data sources differ. -
24
DeepSpeed
Microsoft
FreeDeepSpeed is a deep learning optimization library that is open source for PyTorch. It is designed to reduce memory and computing power, and to train large distributed model with better parallelism using existing computer hardware. DeepSpeed is optimized to provide high throughput and low latency training. DeepSpeed can train DL-models with more than 100 billion parameters using the current generation GPU clusters. It can also train as many as 13 billion parameters on a single GPU. DeepSpeed, developed by Microsoft, aims to provide distributed training for large models. It's built using PyTorch which is a data parallelism specialist. -
25
Quickads.ai
Quickads.ai
$49 per monthQuickads.ai is passionate about helping companies create stunning ads quickly. Our AI-powered platform for quick ads is designed to simplify ad creation, allowing brands and businesses to focus on their core competencies - connecting with target audiences. Our mission is empower businesses of any size to create professional ads without the need for technical or design expertise. We believe every brand deserves effective and eye-catching advertising campaigns that drive engagement, increase brand recognition, and boost sales. We aim to revolutionize advertising by harnessing artificial intelligence. This will make it faster, easier, and more affordable.