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features
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support

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Description

DeepInfer serves as an open-source framework designed for executing DeepSeek language models on Linux platforms that utilize compatible NVIDIA or Huawei Ascend accelerators. It encompasses a variety of features aimed at facilitating offline inference and efficient model execution, including optimized kernels, distributed parallelism, asynchronous batch scheduling, speculative decoding, and the generation of structured outputs in formats like JSON Schema, regular expressions, and EBNF. The project documentation covers support for DeepSeek-V4.1-Flash along with comprehensive guidance on building, configuring, and utilizing examples and evaluation tools. Aimed at developers and infrastructure teams, it assists in constructing or assessing self-managed inference deployments. Additionally, the repository highlights that for production services, there may be a need for supplementary components such as KV-cache, prefill/decode disaggregation, and load-balancing mechanisms that are not part of this particular release, ensuring users are aware of potential additional requirements as they implement the framework. Overall, DeepInfer is designed to optimize the deployment of language models in various contexts, addressing both fundamental and advanced operational needs.

Description

Utilize our Python API to create a prototype for your pipeline, while Towhee takes care of optimizing it for production-ready scenarios. Whether dealing with images, text, or 3D molecular structures, Towhee is equipped to handle data transformation across nearly 20 different types of unstructured data modalities. Our services include comprehensive end-to-end optimizations for your pipeline, encompassing everything from data decoding and encoding to model inference, which can accelerate your pipeline execution by up to 10 times. Towhee seamlessly integrates with your preferred libraries, tools, and frameworks, streamlining the development process. Additionally, it features a pythonic method-chaining API that allows you to define custom data processing pipelines effortlessly. Our support for schemas further simplifies the handling of unstructured data, making it as straightforward as working with tabular data. This versatility ensures that developers can focus on innovation rather than being bogged down by the complexities of data processing.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Python No 

Integrations

Python Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version Yes 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Deployment

Web-Based No 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux Yes 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

DeepSeek

Founded

2023

Country

China

Website

github.com/deepseek-ai/DeepInfer

Vendor Details

Company Name

Towhee

Website

towhee.io

Product Features

Product Features

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

Alternatives

Alternatives

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