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Description

Bitext specializes in creating multilingual hybrid synthetic training datasets tailored for intent recognition and the fine-tuning of language models. These datasets combine extensive synthetic text generation with careful expert curation and detailed linguistic annotation, which encompasses various aspects like lexical, syntactic, semantic, register, and stylistic diversity, all aimed at improving the understanding, precision, and adaptability of conversational models. For instance, their open-source customer support dataset includes approximately 27,000 question-and-answer pairs, totaling around 3.57 million tokens, 27 distinct intents across 10 categories, 30 types of entities, and 12 tags for language generation, all meticulously anonymized to meet privacy, bias reduction, and anti-hallucination criteria. Additionally, Bitext provides industry-specific datasets, such as those for travel and banking, and caters to over 20 sectors in various languages while achieving an impressive accuracy rate exceeding 95%. Their innovative hybrid methodology guarantees that the training data is not only scalable and multilingual but also compliant with privacy standards, effectively reduces bias, and is well-prepared for the enhancement and deployment of language models. This comprehensive approach positions Bitext as a leader in delivering high-quality training resources for advanced conversational AI systems.

Description

Qwen-7B is the 7-billion parameter iteration of Alibaba Cloud's Qwen language model series, also known as Tongyi Qianwen. This large language model utilizes a Transformer architecture and has been pretrained on an extensive dataset comprising web texts, books, code, and more. Furthermore, we introduced Qwen-7B-Chat, an AI assistant that builds upon the pretrained Qwen-7B model and incorporates advanced alignment techniques. The Qwen-7B series boasts several notable features: It has been trained on a premium dataset, with over 2.2 trillion tokens sourced from a self-assembled collection of high-quality texts and codes across various domains, encompassing both general and specialized knowledge. Additionally, our model demonstrates exceptional performance, surpassing competitors of similar size on numerous benchmark datasets that assess capabilities in natural language understanding, mathematics, and coding tasks. This positions Qwen-7B as a leading choice in the realm of AI language models. Overall, its sophisticated training and robust design contribute to its impressive versatility and effectiveness.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Hugging Face
AiAssistWorks
C
CSS
Clojure
Elixir
F#
GaiaNet
Go
HTML
Horay.ai
Java
Kotlin
ModelScope
PHP
Python
SQL
Scala
Sesterce
TypeScript

Integrations

Hugging Face
AiAssistWorks
C
CSS
Clojure
Elixir
F#
GaiaNet
Go
HTML
Horay.ai
Java
Kotlin
ModelScope
PHP
Python
SQL
Scala
Sesterce
TypeScript

Pricing Details

Free
Free Trial
Free Version

Pricing Details

Free
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Bitext

Founded

2008

Country

United States

Website

www.bitext.com/training-datasets/

Vendor Details

Company Name

Alibaba

Founded

1999

Country

China

Website

github.com/QwenLM/Qwen-7B

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