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  1. Stackups
  2. AI
  3. Text & Language Models
  4. Llm Tools
  5. Deepchecks LLM Evaluation vs Roboflow

Deepchecks LLM Evaluation vs Roboflow

OverviewComparisonAlternatives

Overview

Roboflow
Roboflow
Stacks5
Followers6
Votes0
Deepchecks LLM Evaluation
Deepchecks LLM Evaluation
Stacks0
Followers0
Votes0

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Detailed Comparison

Roboflow
Roboflow
Deepchecks LLM Evaluation
Deepchecks LLM Evaluation

It provides all you need to build and deploy computer vision models, from data annotation and organization tools to scalable deployment solutions that work across devices.

Continuously validate your LLM-based application throughout the entire lifecycle from pre-deployment and internal experimentation to production.

Search, curate, and manage visual data; Designed for ultra-fast labeling in the browser; Tools to build accurate models; Deploy custom and foundation models in minutes; Manage annotation projects across multiple work streams
LLM evaluation; Real-time monitoring; Simplify compliance with AI-related policies, regulations, and soft laws
Statistics
Stacks
5
Stacks
0
Followers
6
Followers
0
Votes
0
Votes
0
Integrations
Hugging Face
Hugging Face
Amazon S3
Amazon S3
Zapier
Zapier
Kubernetes
Kubernetes
Amazon Rekognition
Amazon Rekognition
Replit
Replit
Amazon SageMaker
Amazon SageMaker
Google Colaboratory
Google Colaboratory
Google Cloud Run
Google Cloud Run
Google Cloud Vision API
Google Cloud Vision API
Cohere.com
Cohere.com
LangChain
LangChain
Microsoft Azure
Microsoft Azure
OpenAI
OpenAI
Hugging Face
Hugging Face

What are some alternatives to Roboflow, Deepchecks LLM Evaluation?

NanoNets

NanoNets

Build a custom machine learning model without expertise or large amount of data. Just go to nanonets, upload images, wait for few minutes and integrate nanonets API to your application.

Inferrd

Inferrd

It is the easiest way to deploy Machine Learning models. Start deploying Tensorflow, Scikit, Keras and spaCy straight from your notebook with just one extra line.

GraphLab Create

GraphLab Create

Building an intelligent, predictive application involves iterating over multiple steps: cleaning the data, developing features, training a model, and creating and maintaining a predictive service. GraphLab Create does all of this in one platform. It is easy to use, fast, and powerful.

Clever AI Humanizer

Clever AI Humanizer

That transforms AI-generated content into natural, undetectable human-like writing. Bypass AI detection systems with intelligent text humanization technology

LangChain

LangChain

It is a framework built around LLMs. It can be used for chatbots, generative question-answering, summarization, and much more. The core idea of the library is that we can “chain” together different components to create more advanced use cases around LLMs.

Ollama

Ollama

It allows you to run open-source large language models, such as Llama 2, locally.

LlamaIndex

LlamaIndex

It is a project that provides a central interface to connect your LLMs with external data. It offers you a comprehensive toolset trading off cost and performance.

LangGraph

LangGraph

It is a library for building stateful, multi-actor applications with LLMs, built on top of (and intended to be used with) LangChain. It extends the LangChain Expression Language with the ability to coordinate multiple chains (or actors) across multiple steps of computation in a cyclic manner.

BigML

BigML

BigML provides a hosted machine learning platform for advanced analytics. Through BigML's intuitive interface and/or its open API and bindings in several languages, analysts, data scientists and developers alike can quickly build fully actionable predictive models and clusters that can easily be incorporated into related applications and services.

LangSmith

LangSmith

It is a platform for building production-grade LLM applications. It lets you debug, test, evaluate, and monitor chains and intelligent agents built on any LLM framework and seamlessly integrates with LangChain, the go-to open source framework for building with LLMs.

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