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What is LongLLaMA?

This repository presents the research preview for LongLLaMA, an innovative large language model capable of handling extensive contexts, reaching up to 256,000 tokens or potentially even more. Built on the OpenLLaMA framework, LongLLaMA has been fine-tuned using the Focused Transformer (FoT) methodology. The foundational code for this model comes from Code Llama. We are excited to introduce a smaller 3B base version of the LongLLaMA model, which is not instruction-tuned, and it will be released under an open license (Apache 2.0). Accompanying this release is inference code that supports longer contexts, available on Hugging Face. The model's weights are designed to effortlessly integrate with existing systems tailored for shorter contexts, particularly those that accommodate up to 2048 tokens. In addition to these features, we provide evaluation results and comparisons to the original OpenLLaMA models, thus offering a thorough insight into LongLLaMA's effectiveness in managing long-context tasks. This advancement marks a significant step forward in the field of language models, enabling more sophisticated applications and research opportunities.

What is Ling 3.0 Flash?

Ling 3.0 Flash is an evolved language model specifically designed for long-term agent tasks, featuring rapid response capabilities, low activation levels, and reliable tool utilization. With a Mixture-of-Experts architecture, it encompasses an impressive total of 124 billion parameters, activating 5.1 billion parameters for each token, which optimizes its performance while ensuring efficient inference. The model showcases a remarkable native context window of 256K tokens, expandable to a maximum of 1 million tokens, facilitating effective information retrieval from extensive contexts. In comparison to its earlier version, the original Flash model, Ling 3.0 Flash offers superior stability for extended operations, enhances tool-calling accuracy, adheres more closely to instructions, and shows improved compatibility with agent harnesses and coding tasks. Furthermore, its advanced spatial awareness capabilities allow it to construct grids of physical scenes and assess relative positions with precision, while its hybrid reasoning abilities increase success rates across various task complexities. This model not only represents a substantial advancement in language modeling technology but also ensures users can attain exceptional performance across a wide array of applications, thus broadening its potential use cases. Overall, Ling 3.0 Flash stands out as a groundbreaking development in the field, likely to influence future applications significantly.

Media

Media

Integrations Supported

Integrations Supported

Claude Code
Hermes Agent
Kilo Code
OpenClaw
OpenRouter
ZenMux

API Availability

API Availability

Has API

Pricing Information

Free
Free Version

Pricing Information

Pricing not provided
Free Trial Offered?

Supported Platforms

SaaS
On-Prem

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

LongLLaMA

Company Website

github.com/CStanKonrad/long_llama

Company Facts

Organization Name

Ant Group

Date Founded

2014

Company Location

China

Company Website

www.ant-ling.com

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

Large Language Models

Not specified

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

Large Language Models

Not specified

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