Qwen-7B

Qwen-7B

Alibaba
Tinker

Tinker

Thinking Machines Lab
+
+

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About

Qwen-7B is the 7B-parameter version of the large language model series, Qwen (abbr. Tongyi Qianwen), proposed by Alibaba Cloud. Qwen-7B is a Transformer-based large language model, which is pretrained on a large volume of data, including web texts, books, codes, etc. Additionally, based on the pretrained Qwen-7B, we release Qwen-7B-Chat, a large-model-based AI assistant, which is trained with alignment techniques. The features of the Qwen-7B series include: Trained with high-quality pretraining data. We have pretrained Qwen-7B on a self-constructed large-scale high-quality dataset of over 2.2 trillion tokens. The dataset includes plain texts and codes, and it covers a wide range of domains, including general domain data and professional domain data. Strong performance. In comparison with the models of the similar model size, we outperform the competitors on a series of benchmark datasets, which evaluates natural language understanding, mathematics, coding, etc. And more.

About

Tinker is a training API designed for researchers and developers that allows full control over model fine-tuning while abstracting away the infrastructure complexity. It supports primitives and enables users to build custom training loops, supervision logic, and reinforcement learning flows. It currently supports LoRA fine-tuning on open-weight models across both LLama and Qwen families, ranging from small models to large mixture-of-experts architectures. Users write Python code to handle data, loss functions, and algorithmic logic; Tinker handles scheduling, resource allocation, distributed training, and failure recovery behind the scenes. The service lets users download model weights at different checkpoints and doesn’t force them to manage the compute environment. Tinker is delivered as a managed offering; training jobs run on Thinking Machines’ internal GPU infrastructure, freeing users from cluster orchestration.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Large language model developers

Audience

AI researchers and ML engineers requiring a solution to experiment with fine-tuning open source language models while outsourcing infrastructure complexity

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Alibaba
Founded: 1999
China
github.com/QwenLM/Qwen-7B

Company Information

Thinking Machines Lab
United States
thinkingmachines.ai/tinker/

Alternatives

Athene-V2

Athene-V2

Nexusflow

Alternatives

ChatGLM

ChatGLM

Zhipu AI
Mistral 7B

Mistral 7B

Mistral AI
CodeQwen

CodeQwen

Alibaba
LLaMA-Factory

LLaMA-Factory

hoshi-hiyouga
Qwen2

Qwen2

Alibaba

Categories

Categories

Integrations

Python
AiAssistWorks
C#
F#
Go
Horay.ai
Hugging Face
Java
Julia
Kotlin
Llama 3.1
ModelScope
PHP
Qwen Chat
Qwen3
R
Ruby
SQL
Scala
TypeScript

Integrations

Python
AiAssistWorks
C#
F#
Go
Horay.ai
Hugging Face
Java
Julia
Kotlin
Llama 3.1
ModelScope
PHP
Qwen Chat
Qwen3
R
Ruby
SQL
Scala
TypeScript
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