Qwen-7B Description
Qwen-7B, also known as Qwen-7B, is the 7B-parameter variant of the large language models series Qwen. Tongyi Qianwen, proposed by Alibaba Cloud. Qwen-7B, a Transformer-based language model, is pretrained using a large volume data, such as web texts, books, code, etc. Qwen-7B is also used to train Qwen-7B Chat, an AI assistant that uses large models and alignment techniques. The Qwen-7B features include:
Pre-trained with high quality data. We have pretrained Qwen-7B using a large-scale, high-quality dataset that we constructed ourselves. The dataset contains over 2.2 trillion tokens. The dataset contains plain texts and codes and covers a wide range domains including general domain data as well as professional domain data.
Strong performance. We outperform our competitors in a series benchmark datasets that evaluate natural language understanding, mathematics and coding.
And more.
Qwen-7B Alternatives
CodeQwen
CodeQwen, developed by the Qwen Team, Alibaba Cloud, is the code version. It is a transformer based decoder only language model that has been pre-trained with a large number of codes. A series of benchmarks shows that the code generation is strong and that it performs well. Supporting long context generation and understanding with a context length of 64K tokens. CodeQwen is a 92-language coding language that provides excellent performance for text-to SQL, bug fixes, and more. CodeQwen chat is as simple as writing a few lines of code using transformers. We build the tokenizer and model using pre-trained methods and use the generate method for chatting. The chat template is provided by the tokenizer. Following our previous practice, we apply the ChatML Template for chat models. The model will complete the code snippets in accordance with the prompts without any additional formatting.
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ChatGLM
ChatGLM-6B, a Chinese-English bilingual dialogue model based on General Language Model architecture (GLM), has 6.2 billion parameters. Users can deploy model quantization locally on consumer-grade graphic cards (only 6GB video memory required at INT4 quantization levels). ChatGLM-6B is based on technology similar to ChatGPT and optimized for Chinese dialogue and Q&A. After approximately 1T identifiers for Chinese and English bilingual training and supplemented with supervision and fine-tuning as well as feedback self-help and human feedback reinforcement learning, ChatGLM-6B, with 6.2 billion parameters, has been able generate answers that are in line with human preference.
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Qwen2-VL
Qwen2-VL, the latest version in the Qwen model family of vision language models, is based on Qwen2. Qwen2-VL is a newer version of Qwen-VL that has:
SoTA understanding of images with different resolutions & ratios: Qwen2-VL reaches state-of-the art performance on visual understanding benchmarks including MathVista DocVQA RealWorldQA MTVQA etc.
Understanding videos over 20 min: Qwen2-VL is able to understand videos longer than 20 minutes, allowing for high-quality video-based questions, dialogs, content creation, and more.
Agent that can control your mobiles, robotics, etc. Qwen2-VL, with its complex reasoning and decision-making abilities, can be integrated into devices such as mobile phones, robots and other devices for automatic operation using visual environment and text instruction.
Multilingual Support - To serve users worldwide, Qwen2-VL supports texts in other languages within images, besides English or Chinese.
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Qwen
Qwen LLM is a family of large-language models (LLMs), developed by Damo Academy, an Alibaba Cloud subsidiary. These models are trained using a large dataset of text and codes, allowing them the ability to understand and generate text that is human-like, translate languages, create different types of creative content and answer your question in an informative manner.
Here are some of the key features of Qwen LLMs.
Variety of sizes: Qwen's series includes sizes ranging from 1.8 billion parameters to 72 billion, offering options that meet different needs and performance levels.
Open source: Certain versions of Qwen have open-source code, which is available to anyone for use and modification.
Qwen is multilingual and can translate multiple languages including English, Chinese and Japanese.
Qwen models are capable of a wide range of tasks, including text summarization and code generation, as well as generation and translation.
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Pricing
Pricing Starts At:
Free
Pricing Information:
Open source
Free Version:
Yes
Integrations
Company Details
Company:
Alibaba
Year Founded:
1999
Headquarters:
China
Website:
github.com/QwenLM/Qwen-7B
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Product Details
Platforms
SaaS
Windows
Mac
Linux
On-Premises
Type of Training
Documentation
Customer Support
Online
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