Alternatives to Graft

Capture production data. Evaluate outputs together and fine-tune the performance of your LLM. A detailed log overview will help you understand what is happening in production. Work with domain experts, product managers and engineers to create reliable model outputs. Track AI metrics, such as speed, token usage, and quality scores. Copilot automates model evaluations and improvements for your use cases. Create, manage, or optimize prompts for precise and relevant interactions between AI models and users. Compare fine-tuned models and foundation models to improve prompt performance. Build a fine-tuning dataset with your team. Create custom fine-tuning data to optimize model performance.

Amazon SageMaker, a fully managed service, provides data scientists and developers with the ability to quickly build, train, deploy, and deploy machine-learning (ML) models. SageMaker takes the hard work out of each step in the machine learning process, making it easier to create high-quality models. Traditional ML development can be complex, costly, and iterative. This is made worse by the lack of integrated tools to support the entire machine learning workflow. It is tedious and error-prone to combine tools and workflows. SageMaker solves the problem by combining all components needed for machine learning into a single toolset. This allows models to be produced faster and with less effort. Amazon SageMaker Studio is a web-based visual interface that allows you to perform all ML development tasks. SageMaker Studio allows you to have complete control over each step and gives you visibility.

A system that can scale to millions of users, without requiring an engineering team. Create, customize and deploy your chat-based AI. Finance chatbot. xFinance is a 13-billion-parameter model fine-tuned using LoRA. Our goal was show that impressive results can be achieved in financial NLP without breaking the bank. Your own AI assistant to chat with documents. Single or multiple documents. Simple or complex questions. Easy-to-use deep learning platform, hardware efficient algorithms that speed up inference and lower costs. Real-time monitoring and logging of resource usage and cloud costs for deployed models. xTuring, an open-source AI software for personalization, is a powerful tool. xTuring provides a simple interface for personalizing LLMs based on your data and application.

Langtail is a cloud-based development tool designed to streamline the debugging, testing, deployment, and monitoring of LLM-powered applications. The platform provides a no-code interface for debugging prompts, adjusting model parameters, and conducting thorough LLM tests to prevent unexpected behavior when prompts or models are updated. Langtail is tailored for LLM testing, including chatbot evaluations and ensuring reliable AI test prompts. Key features of Langtail allow teams to: • Perform in-depth testing of LLM models to identify and resolve issues before production deployment. • Easily deploy prompts as API endpoints for smooth integration into workflows. • Track model performance in real-time to maintain consistent results in production environments. • Implement advanced AI firewall functionality to control and protect AI interactions. Langtail is the go-to solution for teams aiming to maintain the quality, reliability, and security of their AI and LLM-based applications.

Dynamiq was built for engineers and data scientist to build, deploy and test Large Language Models, and to monitor and fine tune them for any enterprise use case. Key Features: Workflows: Create GenAI workflows using a low-code interface for automating tasks at scale Knowledge & RAG - Create custom RAG knowledge bases in minutes and deploy vector DBs Agents Ops - Create custom LLM agents for complex tasks and connect them to internal APIs Observability: Logging all interactions and using large-scale LLM evaluations of quality Guardrails: Accurate and reliable LLM outputs, with pre-built validators and detection of sensitive content. Fine-tuning : Customize proprietary LLM models by fine-tuning them to your liking

You can use advanced language models and coding to solve a variety of problems. To build cutting-edge applications, leverage large-scale, generative AI models that have deep understandings of code and language to allow for new reasoning and comprehension. These coding and language models can be applied to a variety use cases, including writing assistance, code generation, reasoning over data, and code generation. Access enterprise-grade Azure security and detect and mitigate harmful use. Access generative models that have been pretrained with trillions upon trillions of words. You can use them to create new scenarios, including code, reasoning, inferencing and comprehension. A simple REST API allows you to customize generative models with labeled information for your particular scenario. To improve the accuracy of your outputs, fine-tune the hyperparameters of your model. You can use the API's few-shot learning capability for more relevant results and to provide examples.

Vishwa.ai, an AutoOps Platform for AI and ML Use Cases. It offers expert delivery, fine-tuning and monitoring of Large Language Models. Features: Expert Prompt Delivery : Tailored prompts tailored to various applications. Create LLM Apps without Coding: Create LLM workflows with our drag-and-drop UI. Advanced Fine-Tuning : Customization AI models. LLM Monitoring: Comprehensive monitoring of model performance. Integration and Security Cloud Integration: Supports Google Cloud (AWS, Azure), Azure, and Google Cloud. Secure LLM Integration - Safe connection with LLM providers Automated Observability for efficient LLM Management Managed Self Hosting: Dedicated hosting solutions. Access Control and Audits - Ensure secure and compliant operations.

Optimizing continuous pre-training to enrich models with proprietary data. Assuring domain-specific models provide a smooth user experience. Create a production-friendly RAG pipeline that offers ongoing support. With Arcee's SLM Adaptation system, you do not have to worry about fine-tuning, infrastructure set-up, and all the other complexities involved in stitching together solutions using a plethora of not-built-for-purpose tools. Our product's domain adaptability allows you to train and deploy SLMs for a variety of use cases. Arcee's VPC service allows you to train and deploy your SLMs while ensuring that what belongs to you, stays yours.

Our open-source research efforts are focused on both the new "ware" (middleware and "software" which will wrap and integrate LLMs) as well as building high quality, automation-focused enterprise model available in Hugging Face. LLMWare is also a coherent, high quality, integrated and organized framework for developing LLM-applications in an open system. This provides the foundation for creating LLM-applications that are designed for AI Agent workflows and Retrieval Augmented Generation. Our LLM framework was built from the ground-up to handle complex enterprise use cases. We can provide pre-built LLMs tailored to your industry, or we can fine-tune and customize an LLM for specific domains and use cases. We provide an end-toend solution, from a robust AI framework to specialized models.

Construct your model as a live interactive graph. View data flowing through the architecture of your visualized model. View and edit the model architecture at the atomic level. Graphbook offers X-ray transparency without black boxes. Graphbook checks data type and form in real-time, with clear error messages. This makes model debugging easy. Graphbook abstracts out software dependencies and configuration of the environment, allowing you to focus on your model architecture and data flows with the computing resources required. Cerbrec Graphbook transforms cumbersome AI modeling into a user friendly experience. Graphbook, which is backed by a growing community that includes machine learning engineers and data science experts, helps developers fine-tune their language models like BERT and GPT using text and tabular data. Everything is managed out of box, so you can preview how your model will behave.

Platform for AI agents testing and debugging by the industry's leading developers. We developed the tools, so you don't need to. Visually track events, such as LLM, tools, and agent interactions. Rewind and playback agent runs with pinpoint precision. Keep a complete data trail from prototype to production of logs, errors and prompt injection attacks. Native integrations with top agent frameworks. Track, save and monitor each token that your agent sees. Monitor and manage agent spending using the most recent price monitoring. Save up to 25x on specialized LLMs by fine-tuning them based on completed completions. Build your next agent using evals and replays. You can visualize the behavior of your agents in your AgentOps dashboard with just two lines of coding. After you set up AgentOps each execution of your program will be recorded as a "session" and the data will automatically be recorded for you.

Metal is a fully-managed, production-ready ML retrieval platform. Metal embeddings can help you find meaning in unstructured data. Metal is a managed services that allows you build AI products without having to worry about managing infrastructure. Integrations with OpenAI and CLIP. Easy processing & chunking of your documents. Profit from our system in production. MetalRetriever is easily pluggable. Simple /search endpoint to run ANN queries. Get started for free. Metal API Keys are required to use our API and SDKs. Authenticate by populating headers with your API Key. Learn how to integrate Metal into your application using our Typescript SDK. You can use this library in JavaScript as well, even though we love TypeScript. Fine-tune spp programmatically. Indexed vector data of your embeddings. Resources that are specific to your ML use case.

We are ready to meet all your business needs, whether it is quick engineering, fine-tuning or training. The Together Inference API makes it easy to integrate your new model in your production application. Together AI's elastic scaling and fastest performance allows it to grow with you. To increase accuracy and reduce risks, you can examine how models are created and what data was used. You are the owner of the model that you fine-tune and not your cloud provider. Change providers for any reason, even if the price changes. Store data locally or on our secure cloud to maintain complete data privacy.

The first AI platform for business that does not require any code allows you to train and deploy GPT models in any use case. Our experts are ready to assist you. Our cost-effective tools can be used to fine-tune your open source models using your own data. You can deploy your open source model securely across multiple clouds, without having to rely on a third-party vendor for your valuable data. Our team of experts will create the perfect app for your needs. Our tool allows you to easily monitor your usage, and reduce costs. Let our team of experts help you solve your problems. Automate your customer service and efficiently classify your calls. Our advanced solution allows you to streamline customer interaction and improve service delivery. Build a robust system to detect fraud and anomalies based on previously flagged information.

Choose a model from our open-source collection, run it and access the model API within your product. No matter what model you are using for Image Recognition or Language Processing, all models come pre-trained and packaged with an easy-to use API. There are many models to choose from, and the list is growing. We curate and fine-tune only the best models from HuggingFace or Github. You can either host the model yourself or get your API-Key and endpoint with just one click. Cargoship keeps up with the advancement of AI so you don’t have to. The Cargoship Model Store has a collection that can be used for any ML use case. You can test them in demos and receive detailed guidance on how to implement the model. No matter your level of expertise, our team will pick you up and provide you with detailed instructions.

Build complex backend agents using multiple steps with an action-based orchestration. All LLMs are supported. Build a fully customized UI without writing a line of code for your agent, and serve it on your own domain. Track your agent's every move, literally, to cope with the nondeterministic nature LLMs. Access control can be built at a finer grain for your application, data and agent. A fine-tuned, specialized model to accelerate software development. Automatically handle concurrency and rate limiting.

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.

Fine-tuning is when you take a dataset, and create a model to use AI. This is not always possible without programming so we created a solution in RIku that handles everything in a very easy format. Fine-tuning unlocks an entirely new level of power for artificial intelligence and we are excited to help you explore this. Public Share Links are landing pages you can create for any of the prompts. These can be designed with your brand in mind, including colors and adding your logo. These links can be shared with anyone, and if they have access to the password to unlock it they will be able make generations. No-code assistant builder for your audience. We found that projects using multiple large languages models have a lot of problems. They all return their outputs in a slightly different way.

We power customized and scalable generative artificial intelligence for the world's largest institutions. We provide institutions with category-leading tools and infrastructure to integrate their private and relevant public data, allowing them to leverage commercial generative AI in a way they could not before. Access in-depth analytics and understand how your AI can add value. Autonomous model tuning: Watch as your AI improves itself, fine-tuning performance based on data in real-time and user interactions. Control AI costs precisely, from the overall budget to the individual API key usage. Chi Core will transform your AI journey, simplify and increase the value of AI roadmaps, while seamlessly integrating cutting edge AI into your business technology stack.

Simplismart’s fastest inference engine allows you to fine-tune and deploy AI model with ease. Integrate with AWS/Azure/GCP, and many other cloud providers, for simple, scalable and cost-effective deployment. Import open-source models from popular online repositories, or deploy your custom model. Simplismart can host your model or you can use your own cloud resources. Simplismart allows you to go beyond AI model deployment. You can train, deploy and observe any ML models and achieve increased inference speed at lower costs. Import any dataset to fine-tune custom or open-source models quickly. Run multiple training experiments efficiently in parallel to speed up your workflow. Deploy any model to our endpoints, or your own VPC/premises and enjoy greater performance at lower cost. Now, streamlined and intuitive deployments are a reality. Monitor GPU utilization, and all of your node clusters on one dashboard. On the move, detect any resource constraints or model inefficiencies.

Klu.ai, a Generative AI Platform, simplifies the design, deployment, and optimization of AI applications. Klu integrates your Large Language Models and incorporates data from diverse sources to give your applications unique context. Klu accelerates the building of applications using language models such as Anthropic Claude (Azure OpenAI), GPT-4 (Google's GPT-4), and over 15 others. It allows rapid prompt/model experiments, data collection and user feedback and model fine tuning while cost-effectively optimising performance. Ship prompt generation, chat experiences and workflows in minutes. Klu offers SDKs for all capabilities and an API-first strategy to enable developer productivity. Klu automatically provides abstractions to common LLM/GenAI usage cases, such as: LLM connectors and vector storage, prompt templates, observability and evaluation/testing tools.

Our platform allows you to create AI products, train, fine-tune, and deploy models on the cloud. You don't have to worry about scaling, infrastructure, cost management, or other technical issues. Prebuilt, fully customizable modular components make it easy to train, fine tune, and deploy models. The science, not the engineering, should be your focus. Lightning components organize code to run on the cloud and manage its own infrastructure, cloud cost, and other details. 50+ optimizations to lower cloud cost and deliver AI in weeks, not months. Enterprise-grade control combined with consumer-level simplicity allows you to optimize performance, reduce costs, and take on less risk. Get more than a demo. In days, not months, you can launch your next GPT startup, diffusion startup or cloud SaaSML service.

Train, fine-tune and generate text and image AI based on your data. We use the best open-source models for image and text generation, and can train them within minutes using LoRA fine tuning. Click the share button to generate a link or bot to your session. You can deploy your own private infrastructure. Create a free Stable Diffusion XL account to start chatting and generating images using open source language models. Drag'n'drop is the easiest way to fine-tune your model using your own text or images. It takes between 3-10 minutes. You can chat with the models and create images using a familiar chat interface.

Create, evaluate, deploy, refine, and improve custom natural language processing models. Your team can automate workflows without the need for an AI expert team or expensive infrastructure. Metatext makes it easy to create customized AI/NLP models without any prior knowledge of ML, data science or MLOps. Automate complex workflows in just a few steps and rely on intuitive APIs and UIs to handle the heavy lifting. Our APIs will handle all the heavy lifting. Your custom AI will be trained and deployed automatically. A set of deep learning algorithms will help you get the most out of your custom AI. You can test it in a Playground. Integrate our APIs into your existing systems, Google Spreadsheets, or other tools. Choose the AI engine that suits your needs. Each AI engine offers a variety of tools that can be used to create datasets and fine tune models. Upload text data in different file formats and use our AI-assisted data labeling tool to annotate labels.

Entry Point AI is a modern AI optimization platform that optimizes proprietary and open-source language models. Manage prompts and fine-tunes in one place. We make it easy to fine-tune models when you reach the limits. Fine-tuning involves showing a model what to do, not telling it. It works in conjunction with prompt engineering and retrieval augmented generation (RAG) in order to maximize the potential of AI models. Fine-tuning your prompts can help you improve their quality. Imagine it as an upgrade to a few-shot model that incorporates the examples. You can train a model to perform at the same level as a high-quality model for simpler tasks. This will reduce latency and costs. For safety, to protect the brand, or to get the formatting correct, train your model to not respond in a certain way to users. Add examples to your dataset to cover edge cases and guide model behavior.

Powerful language models a click away. Join over 8,000 developers in building the next wave world-changing applications. Fine-tune GPT-J and deploy Codegen, FLAN-T5, GPT NeoX and GPT NeoX. There are multiple models with different capabilities and prices. GPT-J has the fastest speed, while GPT NeoX is the most powerful. And more models are coming. These models can be used for classification, entity extracting, code generation and chatbots. They can also be used for content generation, summarizations, paraphrasings, sentiment analysis and more. These models have already been pre-trained using a large amount of text taken from the internet. The fine-tuning process improves this for specific tasks, by training on more examples than are possible in a prompt. This allows you to achieve better results across a range of tasks.

A simple web API allows you to fine-tune your LLMs and receive completions. No infrastructure is required. Instantly create private AI applications that comply with SOC2-standards. Our developer platform makes it easy to customize models for your specific use case. Select the base model and define the data that you want to teach. We will take care of everything else. With a single API, you can integrate private LLMs with your applications. No more deployment, orchestration or infrastructure headaches. The most powerful OSS available -- highly generalized capabilities with amazing storytelling and reasoning capabilities. Use a fully unlocked LLM for the best internal automation systems in your company.

Google AI Studio is an online tool that's free and allows individuals and small groups to create apps and chatbots by using natural language prompting. It allows users to create API keys and prompts for app development. Google AI Studio allows users to discover Gemini Pro's APIs, create prompts and fine-tune Gemini. It also offers generous free quotas, allowing 60 requests a minute. Google has also developed a Generative AI Studio based on Vertex AI. It has models of various types that allow users to generate text, images, or audio content.

Query and compare multiple proprietary and open-source models simultaneously. Replace expensive APIs with custom AI models. Customize foundational AI models using your private data and adapt them to fit your specific use case. Small, fine-tuned models perform at the same level as GPT-4 while being up to 90% less expensive. Airtrain's LLM-assisted scoring simplifies model grading using your task descriptions. Airtrain's API allows you to serve your custom models in the cloud, or on your own secure infrastructure. Evaluate and compare proprietary and open-source models across your entire dataset using custom properties. Airtrain's powerful AI evaluation tools let you score models based on arbitrary properties to create a fully customized assessment. Find out which model produces outputs that are compliant with the JSON Schema required by your agents or applications. Your dataset is scored by models using metrics such as length and compression.

Describe examples of API requests and responses. Define API logic in natural language. Test your API endpoints, and fine-tune prompt, response structure, or request structure. Integrate API endpoints into your applications with just a click. In less than one minute, you can build and deploy sophisticated application logic with no code. No need for individual LLM accounts. Sign up for Backengine and get started building. Our super-fast backend architecture is available immediately. All endpoints have been secured and protected, so that only you and your application can use them. Manage your team members easily so that everyone can work on Backengine endpoints. Add persistent data to your Backengine endpoints. A complete replacement for the backend. Use external APIs to integrate your endpoints.

With our enterprise Gen AI stack you can go beyond your imagination. You can instantly offload manual tasks and give them to powerful assistants. The sky is the limit. For enterprises that place data security first, fine-tune generative AI models and deploy them on your own cloud securely.

We'll host your website so you can focus on building. Our rest API is easy to use. No limits, no headaches. We have all the information you need. Don't pay for nothing. We only charge for use. Our support team is also our tech team. You'll get support directly, not through a series of hoops. Our flexible infrastructure allows us scale with you as your business grows and can handle spikes in activity. Our stable diffusion API allows you to easily create images and art from text to image, or image to image. Additional models allow you to change the output's style. MJ v4, Any v3, Analog and Redshift, and many more. Other stable diffusion versions such as 2.0+ will also include. You can train your own stable diffusion model (fine tuning) and then deploy on Evoke via an API. In the future, we will have models such as Whisper, Yolo and GPT-J. We also plan to offer training and deployment on many other models.

With just one line of code, you can deploy all major ML frameworks like Pytorch and Onnx. Do you not have your own models? Prebuilt models can be deployed to reduce latency and cost. You can fine-tune models for specific tasks to reduce latency and costs while increasing performance. It's easy to do and you don't have to worry about infrastructure. Integrate with the top ML observability platform to be alerted on feature or prediction drift, compare models versions, and resolve issues quickly. To resolve model performance problems, discover the root causes of prediction and feature drift. Find out which features contribute the most to your model's performance.

OpenPipe provides fine-tuning for developers. Keep all your models, datasets, and evaluations in one place. New models can be trained with a click of a mouse. Automatically record LLM responses and requests. Create datasets using your captured data. Train multiple base models using the same dataset. We can scale your model to millions of requests on our managed endpoints. Write evaluations and compare outputs of models side by side. You only need to change a few lines of code. OpenPipe API Key can be added to your Python or Javascript OpenAI SDK. Custom tags make your data searchable. Small, specialized models are much cheaper to run than large, multipurpose LLMs. Replace prompts in minutes instead of weeks. Mistral and Llama 2 models that are fine-tuned consistently outperform GPT-4-1106 Turbo, at a fraction the cost. Many of the base models that we use are open-source. You can download your own weights at any time when you fine-tune Mistral or Llama 2.

Haystack’s pipeline architecture allows you to apply the latest NLP technologies to your data. Implement production-ready semantic searching, question answering and document ranking. Evaluate components and fine tune models. Haystack's pipelines allow you to ask questions in natural language, and find answers in your documents with the latest QA models. Perform semantic search to retrieve documents ranked according to meaning and not just keywords. Use and compare the most recent transformer-based language models, such as OpenAI's GPT-3 and BERT, RoBERTa and DPR. Build applications for semantic search and question answering that can scale up to millions of documents. Building blocks for the complete product development cycle, including file converters, indexing, models, labeling, domain adaptation modules and REST API.

You can choose from our library and fine-tune or create your own capabilities to analyze, process, and present text, audio, and video at large scale. Incorporate advanced NLP in your app or workflow. You can choose from the existing library or create your own. With just one API call, you can summarize, tag, and analyze language using stackable, composable NLP blocks. These blocks are built on state of the art models. Our powerful Custom-Skill engine allows you to create and fine-tune custom Language skills from your data. Only 5% of the world’s population can speak English as their first language. One AI's capabilities can be used in multiple languages. You can build a podcast platform, CRM or content publishing tool using One AI's multilingual capabilities.

GPT can be fine-tuned without any technical knowledge. AI models can be improved by customizing them to meet your needs. Prompteasy.ai allows you to fine-tune AI in just a few seconds. We help you fine-tune AI to suit your needs. You don't need to know anything about AI fine-tuning. Our AI models will handle everything. As part of our initial launch, we will offer prompteasy free. Pricing plans will be released later this year. Our vision is that AI will be accessible to everyone. We believe the real power of AI is in the way we train and orchestrate foundational models as opposed to using them off-the-shelf. Upload relevant materials, and then interact with our AI using natural language. We build the dataset for you. You can chat with AI, download datasets, and fine-tune GPT.

It's not enough to just look at a few examples. To get actionable insights about how to improve your models, gather feedback from end-users at large. With the GPT improvement engine, you can easily A/B test models. You can only go so far with prompts. Fine-tuning your best data will produce better results. No coding or data science required. Integration in one line of code You can experiment with ChatGPT, Claude and other language model providers without having to touch it again. If you have the right tools to customize models for your customers, you can build innovative and defensible products on top APIs. Copy AI allows you to fine tune models based on the best data. This will allow you to save money and give you a competitive edge. This technology allows for magical product experiences that delight more than 2 million users.

The Xilinx AI development platform for AI Inference on Xilinx hardware platforms consists optimized IP, tools and libraries, models, examples, and models. It was designed to be efficient and easy-to-use, allowing AI acceleration on Xilinx FPGA or ACAP. Supports mainstream frameworks as well as the most recent models that can perform diverse deep learning tasks. A comprehensive collection of pre-optimized models is available for deployment on Xilinx devices. Find the closest model to your application and begin retraining! This powerful open-source quantizer supports model calibration, quantization, and fine tuning. The AI profiler allows you to analyze layers in order to identify bottlenecks. The AI library provides open-source high-level Python and C++ APIs that allow maximum portability from the edge to the cloud. You can customize the IP cores to meet your specific needs for many different applications.

FinetuneFast allows you to fine-tune AI models, deploy them quickly and start making money online. Here are some of the features that make FinetuneFast unique: - Fine tune your ML models within days, not weeks - The ultimate ML boilerplate, including text-to-images, LLMs and more - Build your AI app to start earning online quickly - Pre-configured scripts for efficient training of models - Efficient data load pipelines for streamlined processing Hyperparameter optimization tools to improve model performance - Multi-GPU Support out of the Box for enhanced processing power - No-Code AI Model fine-tuning for simple customization - Model deployment with one-click for quick and hassle free deployment - Auto-scaling Infrastructure for seamless scaling of your models as they grow - API endpoint creation for easy integration with other system - Monitoring and logging for real-time performance monitoring

Generative AI (GAI) and Large Language Models, or LLMs, are promising solutions to unlock the value of unstructured information. They provide enterprises with instant insights. This has given businesses the opportunity to reimagine their customer experience, products and services, as well as increase productivity within their teams. baioniq, Quantiphi’s enterprise-ready Generative AI Platform for AWS, is designed to help organizations quickly adopt generative AI capabilities. AWS customers can deploy baioniq on AWS using a containerized version. It is a modular solution which allows modern enterprises to fine tune LLMs in four simple steps to incorporate domain-specific information and perform enterprise-specific functions.

We have just launched the X1 large model series. Giga ML’s most powerful model can be used for pre-training, fine-tuning and on-prem deployment. We are Open AI compliant, so your existing integrations, such as long chain, llama index, and others, will work seamlessly. You can continue to pre-train LLM's using domain-specific databooks or docs, or company documents. The world of large-scale language models (LLMs), which offer unprecedented opportunities for natural language process across different domains, is rapidly expanding. Despite this, there are still some critical challenges that remain unresolved. Giga ML proudly introduces the X1 Large model 32k, a pioneering LLM solution on-premise that addresses these critical challenges.

Your platform for developing generative AI and custom copilots. Use pre-built and customizable AI model on your data to build solutions faster. Explore a growing collection of models, both open-source and frontier-built, that are pre-built and customizable. Create AI models using a code first experience and an accessible UI validated for accessibility by developers with disabilities. Integrate all your OneLake data into Microsoft Fabric. Integrate with GitHub codespaces, Semantic Kernel and LangChain. Build apps quickly with prebuilt capabilities. Reduce wait times by personalizing content and interactions. Reduce the risk for your organization and help them discover new things. Reduce the risk of human error by using data and tools. Automate operations so that employees can focus on more important tasks.

Lamini allows enterprises to transform proprietary data into next-generation LLM capabilities by offering a platform that allows in-house software teams the opportunity to upgrade to OpenAI level AI teams, and build within the security provided by their existing infrastructure. Optimised JSON decoding guarantees a structured output. Fine-tuning retrieval-augmented retrieval to improve photographic memory. Improve accuracy and reduce hallucinations. Inferences for large batches can be highly parallelized. Parameter-efficient finetuning for millions of production adapters. Lamini is the sole company that allows enterprise companies to develop and control LLMs safely and quickly from anywhere. It uses the latest research and technologies to create ChatGPT, which was developed from GPT-3. These include, for example, fine-tuning and RLHF.

The first hardware and software computing protocol that integrates both to train and fine tune your AI models. Reduce your training costs up to 80%. Deploy your model in seconds using open-source template models or bring your model. Debug containers easily with GPU, CPU and Memory metrics. You can monitor logs live. You can track all models and training set with cryptographic proofs to ensure complete accountability. You can control the entire training process with just a few commands. You can earn block rewards by adding your computer to the networking. Track key metrics like connectivity and uptime.

Test, launch and refine Gen AI prompting. RAG Agents. Datasets. Workflows. A single workspace for Engineers and Product Managers to explore LLM technology.

Instill Core is a powerful AI infrastructure tool that orchestrates data, models, and pipelines, allowing for the rapid creation of AI-first apps. Instill Cloud is available or you can self-host from the instill core GitHub repository. Instill Core includes Instill VDP: Versatile Data Pipeline, designed to address unstructured data ETL problems and provide robust pipeline orchestration. Instill Model: A MLOps/LLMOps Platform that provides seamless model serving, fine tuning, and monitoring to ensure optimal performance with unstructured ETL. Instill Artifact: Facilitates orchestration of data for unified unstructured representation. Instill Core simplifies AI workflows and makes them easier to manage. It is a must-have for data scientists and developers who use AI technologies.

We've been working on Generative AI for 5 years. Deep Lake combines the power and flexibility of vector databases and data lakes to create enterprise-grade LLM-based solutions and refine them over time. Vector search does NOT resolve retrieval. You need a serverless search for multi-modal data including embeddings and metadata to solve this problem. You can filter, search, and more using the cloud, or your laptop. Visualize your data and embeddings to better understand them. Track and compare versions to improve your data and your model. OpenAI APIs are not the foundation of competitive businesses. Your data can be used to fine-tune LLMs. As models are being trained, data can be efficiently streamed from remote storage to GPUs. Deep Lake datasets can be visualized in your browser or Jupyter Notebook. Instantly retrieve different versions and materialize new datasets on the fly via queries. Stream them to PyTorch, TensorFlow, or Jupyter Notebook.

Unlock prices that are 3-5x higher than those of traditional clouds. FluidStack aggregates GPUs from data centres around the world that are underutilized to deliver the best economics in the industry. Deploy up to 50,000 high-performance servers within seconds using a single platform. In just a few days, you can access large-scale A100 or H100 clusters using InfiniBand. FluidStack allows you to train, fine-tune and deploy LLMs for thousands of GPUs at affordable prices in minutes. FluidStack unifies individual data centers in order to overcome monopolistic GPU pricing. Cloud computing can be made more efficient while allowing for 5x faster computation. Instantly access over 47,000 servers with tier four uptime and security through a simple interface. Train larger models, deploy Kubernetes Clusters, render faster, and stream without latency. Setup with custom images and APIs in seconds. Our engineers provide 24/7 direct support through Slack, email, or phone calls.

Production-ready AI models that are fast and accurate. High-availability inference API that leverages the most advanced NVIDIA GPUs. We have selected the most popular open-source natural language processing models (NLP) and deployed them for the community. You can fine-tune your models (including GPT-J) or upload your custom models. Then, deploy them to production. Upload your AI models, including GPT-J, to your dashboard and immediately use them in production.