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Batch LLM Inference is better with Sutro

Run LLM Batch Jobs in Hours, Not Days, at a Fraction of the Cost.

Get Started

Generate a question/answer pair for the following chunk of vLLM documentation

Inputs

Outputs

Intro to vLLM

vLLM is a fast and easy-to-use library for LLM inference and serving. Originally developed in the Sky Computing Lab at UC Berkeley, vLLM has evolved into a community-driven project with contributions from both academia and industry.

Loading Models

vLM models can be loaded in two different ways. To pass a loaded model into the vLLM framework for further processing and inference without reloading it from disk or a model hub, first start by generating


Using the Open AI Server

Run:ai Model Streamer is a library to read tensors in concurrency, while streaming it to GPU memory. Further reading can be found in Run:ai Model Streamer Documentation.

vLLM supports loading weights in Safetensors format using the Run:ai Model Streamer. You first need to install vLLM RunAI optional dependency:

Question: Is vLLM compatible with all open-source models? ...

Question: How do I load a custom model from HuggingFace? ...

Question: Can I use the OpenAI compatible server to replace calls...

+128 more…

Batch LLM Inference is better with Sutro

Run LLM Batch Jobs in Hours, Not Days, at a Fraction of the Cost.

Get Started

Generate a question/answer pair for the following chunk of vLLM documentation

Inputs

Outputs

Intro to vLLM

vLLM is a fast and easy-to-use library for LLM inference and serving. Originally developed in the Sky Computing Lab at UC Berkeley, vLLM has evolved into a community-driven project with contributions from both academia and industry.

Loading Models

vLM models can be loaded in two different ways. To pass a loaded model into the vLLM framework for further processing and inference without reloading it from disk or a model hub, first start by generating


Using the Open AI Server

Run:ai Model Streamer is a library to read tensors in concurrency, while streaming it to GPU memory. Further reading can be found in Run:ai Model Streamer Documentation.

vLLM supports loading weights in Safetensors format using the Run:ai Model Streamer. You first need to install vLLM RunAI optional dependency:

Question: Is vLLM compatible with all open-source models? ...

Question: How do I load a custom model from HuggingFace? ...

Question: Can I use the OpenAI compatible server to replace calls...

+128 more…

Lead scoring

Effortlessly score your entire lead pipeline at a fraction of the cost

Use Sutro to run large-scale batch jobs that enrich and score leads. Turn millions of unstructured data points into qualified prospects without the complexity or cost of managing your own infrastructure.

Get Access

Generate a question/answer pair for the following chunk of vLLM documentation

Inputs

Outputs

Intro to vLLM

vLLM is a fast and easy-to-use library for LLM inference and serving. Originally developed in the Sky Computing Lab at UC Berkeley, vLLM has evolved into a community-driven project with contributions from both academia and industry.

Loading Models

vLM models can be loaded in two different ways. To pass a loaded model into the vLLM framework for further processing and inference without reloading it from disk or a model hub, first start by generating


Using the Open AI Server

Run:ai Model Streamer is a library to read tensors in concurrency, while streaming it to GPU memory. Further reading can be found in Run:ai Model Streamer Documentation.

vLLM supports loading weights in Safetensors format using the Run:ai Model Streamer. You first need to install vLLM RunAI optional dependency:

Question: Is vLLM compatible with all open-source models? ...

Question: How do I load a custom model from HuggingFace? ...

Question: Can I use the OpenAI compatible server to replace calls...

+128 more…

Batch LLM Inference is better with Sutro

Run LLM Batch Jobs in Hours, Not Days, at a Fraction of the Cost.

Get Started

Generate a question/answer pair for the following chunk of vLLM documentation

Inputs

Outputs

Intro to vLLM

vLLM is a fast and easy-to-use library for LLM inference and serving. Originally developed in the Sky Computing Lab at UC Berkeley, vLLM has evolved into a community-driven project with contributions from both academia and industry.

Loading Models

vLM models can be loaded in two different ways. To pass a loaded model into the vLLM framework for further processing and inference without reloading it from disk or a model hub, first start by generating


Using the Open AI Server

Run:ai Model Streamer is a library to read tensors in concurrency, while streaming it to GPU memory. Further reading can be found in Run:ai Model Streamer Documentation.

vLLM supports loading weights in Safetensors format using the Run:ai Model Streamer. You first need to install vLLM RunAI optional dependency:

Question: Is vLLM compatible with all open-source models? ...

Question: How do I load a custom model from HuggingFace? ...

Question: Can I use the OpenAI compatible server to replace calls...

+128 more…

Batch LLM Inference is better with Sutro

Run LLM Batch Jobs in Hours, Not Days, at a Fraction of the Cost.

Get Started

Generate a question/answer pair for the following chunk of vLLM documentation

Inputs

Outputs

Intro to vLLM

vLLM is a fast and easy-to-use library for LLM inference and serving. Originally developed in the Sky Computing Lab at UC Berkeley, vLLM has evolved into a community-driven project with contributions from both academia and industry.

Loading Models

vLM models can be loaded in two different ways. To pass a loaded model into the vLLM framework for further processing and inference without reloading it from disk or a model hub, first start by generating


Using the Open AI Server

Run:ai Model Streamer is a library to read tensors in concurrency, while streaming it to GPU memory. Further reading can be found in Run:ai Model Streamer Documentation.

vLLM supports loading weights in Safetensors format using the Run:ai Model Streamer. You first need to install vLLM RunAI optional dependency:

Question: Is vLLM compatible with all open-source models? ...

Question: How do I load a custom model from HuggingFace? ...

Question: Can I use the OpenAI compatible server to replace calls...

+128 more…

From Raw Leads to Scored Pipeline, Simplified

Sutro takes the pain away from testing and scaling LLM batch jobs to unblock your most ambitious sales and marketing projects.

import sutro as so

from pydantic import BaseModel

class ReviewClassifier(BaseModel):

sentiment: str

user_reviews = '.

User_reviews.csv

User_reviews-1.csv

User_reviews-2.csv

User_reviews-3.csv

system_prompt = 'Classify the review as positive, neutral, or negative.'

results = so.infer(user_reviews, system_prompt, output_schema=ReviewClassifier)

Progress: 1% | 1/514,879 | Input tokens processed: 0.41m, Tokens generated: 591k

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Prototype

Start small and iterate fast on your lead scoring workflows. Accelerate experiments by testing on Sutro before committing to large jobs.

Scale

Scale your LLM workflows so your team can do more in less time. Process billions of tokens in hours, not days, with no infrastructure headaches or exploding costs.

Integrate

Seamlessly connect Sutro to your existing LLM workflows. Sutro's Python SDK is compatible with popular data orchestration tools, like Airflow and Dagster.

Scale your lead scoring effortlessly

Confidently handle millions of requests, and billions of tokens at a time without the pain of managing infrastructure. Go from raw lead data to a fully scored pipeline in a single batch job.

Reduce costs by 10x or more

Reduce costs by 10x or more

Reduce costs by 10x or more

Get results faster and reduce lead scoring costs by parallelizing your LLM calls through Sutro. Stop overpaying for real-time inference when batch processing is all you need.

Shorten development cycles

Rapidly prototype your lead scoring models. Get feedback from large batch jobs in as little as minutes before committing to scoring your entire database.

Personalized email generation

Longer description goes here, should span multiple lines.

Contact info extraction

Transform unstructured data from sources like web pages into structured insights that enrich your CRM entries.

Sales call analysis

Convert massive amounts of free-form text from call transcripts into analytics-ready datasets to unlock insights.

Sentiment analysis

Automatically organize your data into meaningful categories without involving your ML engineer.

Structured Extraction

Crawl millions of web pages, and extract analytics-ready datasets for your company or your customers.

Customer review analysis

Easily sift through thousands of product reviews and unlock valuable product insights while brewing your morning coffee.

Personalized email generation

Longer description goes here, should span multiple lines.

Contact info extraction

Transform unstructured data from sources like web pages into structured insights that enrich your CRM entries.

Sales call analysis

Convert massive amounts of free-form text from call transcripts into analytics-ready datasets to unlock insights.

Sentiment analysis

Automatically organize your data into meaningful categories without involving your ML engineer.

Structured Extraction

Crawl millions of web pages, and extract analytics-ready datasets for your company or your customers.

Customer review analysis

Easily sift through thousands of product reviews and unlock valuable product insights while brewing your morning coffee.

Personalized email generation

Longer description goes here, should span multiple lines.

Contact info extraction

Transform unstructured data from sources like web pages into structured insights that enrich your CRM entries.

Sales call analysis

Convert massive amounts of free-form text from call transcripts into analytics-ready datasets to unlock insights.

Sentiment analysis

Automatically organize your data into meaningful categories without involving your ML engineer.

Structured Extraction

Crawl millions of web pages, and extract analytics-ready datasets for your company or your customers.

Customer review analysis

Easily sift through thousands of product reviews and unlock valuable product insights while brewing your morning coffee.

FAQ

What is Sutro?

What kinds of tasks can I do with Sutro?

How does Sutro help reduce costs?

How do I integrate Sutro into my existing workflow?

How does Sutro handle large-scale jobs?

What Will You Scale with Sutro?

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