Top 10 Github Vllm Alternatives & Competitors

(2)4.8 out of 5

If you are considering Github Vllm, you may also want to investigate similar alternatives or competitors to find the best solution. Other important factors to consider when researching alternatives to Github Vllm include ease of use and reliability. The best overall Github Vllm alternative is LaunchDarkly. Other similar apps like Github Vllm are Vertex AI, Botpress, IBM watsonx Orchestrate, and Kong Gateway. Github Vllm alternatives can be found in Large Language Model Operationalization (LLMOps) Software but may also be in Data Science and Machine Learning Platforms or Feature Management Software.

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Best Paid & Free Alternatives to Github Vllm

LaunchDarkly
Vertex AI
Botpress
IBM watsonx Orchestrate
Kong Gateway
SuperAnnotate
Dataiku
IBM watsonx.ai

Top 10 Alternatives to Github Vllm Recently Reviewed By G2 Community

Browse options below. Based on reviewer data, you can see how Github Vllm stacks up to the competition, check reviews from current & previous users in industries like Computer Software and Information Technology and Services, and find the best product for your business.

Product Description

Categories in common with Github Vllm:

Large Language Model Operationalization (LLMOps)

Vertex AI

By Google

4.3/5

(634)

Product Description

Vertex AI is a managed machine learning (ML) platform that helps you build, train, and deploy ML models faster and easier. It includes a unified UI for the entire ML workflow, as well as a variety of tools and services to help you with every step of the process. Vertex AI Workbench is a cloud-based IDE that is included with Vertex AI. It makes it easy to develop and debug ML code. It provides a variety of features to help you with your ML workflow, such as code completion, linting, and debugging. Vertex AI and Vertex AI Workbench are a powerful combination that can help you accelerate your ML development. With Vertex AI, you can focus on building and training your models, while Vertex AI Workbench takes care of the rest. This frees you up to be more productive and creative, and it helps you get your models into production faster. If you're looking for a powerful and easy-to-use ML platform, then Vertex AI is a great option. With Vertex AI, you can build, train, and deploy ML models faster and easier than ever before.

Categories in common with Github Vllm:

Large Language Model Operationalization (LLMOps)

Botpress

By Botpress

4.5/5

(462)

Product Description

Botpress is a user-friendly conversational AI platform that empowers individuals and teams of all sizes to design, build, and deploy AI-powered chatbots for various applications. As a pioneer in the chatbot industry, Botpress embraces the power of large language models (LLM) and generative AI to create personalized, engaging chatbot experiences for any purpose. Available in 100+ languages and with a GPT-native suite of tools to help you unlock your creativity, Botpress supports you in achieving your conversation automation goals.

Categories in common with Github Vllm:

Large Language Model Operationalization (LLMOps)

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Kong Gateway

By Kong Inc

4.4/5

(269)

Product Description

Categories in common with Github Vllm:

Large Language Model Operationalization (LLMOps)

Product Description

Categories in common with Github Vllm:

Large Language Model Operationalization (LLMOps)

Dataiku

By Dataiku

4.4/5

(188)

Product Description

Categories in common with Github Vllm:

Large Language Model Operationalization (LLMOps)

IBM watsonx.ai

By IBM

4.4/5

(133)

Product Description

Categories in common with Github Vllm:

Large Language Model Operationalization (LLMOps)

Azure Machine Learning

By Microsoft

4.3/5

(88)

Product Description

Azure Machine Learning is an enterprise-grade service that facilitates the end-to-end machine learning lifecycle, enabling data scientists and developers to build, train, and deploy models efficiently. Key Features and Functionality: - Data Preparation: Quickly iterate data preparation on Apache Spark clusters within Azure Machine Learning, interoperable with Microsoft Fabric. - Feature Store: Increase agility in shipping your models by making features discoverable and reusable across workspaces. - AI Infrastructure: Take advantage of purpose-built AI infrastructure uniquely designed to combine the latest GPUs and InfiniBand networking. - Automated Machine Learning: Rapidly create accurate machine learning models for tasks including classification, regression, vision, and natural language processing. - Responsible AI: Build responsible AI solutions with interpretability capabilities. Assess model fairness through disparity metrics and mitigate unfairness. - Model Catalog: Discover, fine-tune, and deploy foundation models from Microsoft, OpenAI, Hugging Face, Meta, Cohere, and more using the model catalog. - Prompt Flow: Design, construct, evaluate, and deploy language model workflows with prompt flow. - Managed Endpoints: Operationalize model deployment and scoring, log metrics, and perform safe model rollouts. Primary Value and Solutions Provided: Azure Machine Learning accelerates time to value by streamlining prompt engineering and machine learning model workflows, facilitating faster model development with powerful AI infrastructure. It streamlines operations by enabling reproducible end-to-end pipelines and automating workflows with continuous integration and continuous delivery (CI/CD). The platform ensures confidence in development through unified data and AI governance with built-in security and compliance, allowing compute to run anywhere for hybrid machine learning. Additionally, it promotes responsible AI by providing visibility into models, evaluating language model workflows, and mitigating fairness, biases, and harm with built-in safety systems.

Categories in common with Github Vllm:

Large Language Model Operationalization (LLMOps)