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Shenzhen Cyber Affairs Department Takes Action! Tianyan and Tiqu AI Are Rectified for Vulgar Content

9k 4 minutes ago
Shenzhen Cyber Affairs Department Takes Action! Tianyan and Tiqu AI Are Rectified for Vulgar Content

Kechang Xunfei's Large Model Training Speeds Up Again! Domestic Computing Power Has Reached A100 Level!

9.5k 4 minutes ago
Kechang Xunfei's Large Model Training Speeds Up Again! Domestic Computing Power Has Reached A100 Level!

Zhejiang Mobile x Huawei Wins the IPv6 Innovation Competition! SPN+AI Creates a Deterministic Intelligent Network to Empower the Digital Transformation of Various Industries

7.2k 5 hours ago
Zhejiang Mobile x Huawei Wins the IPv6 Innovation Competition! SPN+AI Creates a Deterministic Intelligent Network to Empower the Digital Transformation of Various Industries

Huawei Cloud Embodied Robot Chief Zhu Senhua Leaves to Start His Own Business, Exploring Brain Cognition Technology

8.7k 8 hours ago
Huawei Cloud Embodied Robot Chief Zhu Senhua Leaves to Start His Own Business, Exploring Brain Cognition Technology

AI Products

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Xiaoyi

Xiaoyi is a smart assistant launched by Huawei, offering a variety of AI services such as chatting, writing, and programming.

Personal assistant
14.7k

mindspore.cn

Huawei's open-source, self-developed AI framework

AI development assistant
9.4k

Huawei Cloud AI Platform

Provides developers with a one-stop service encompassing resource tools, application practices, monetization, learning and exchange, and competition activities.

AI development assistant
12.3k

Models

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Pangu-NLP-N2-128K-5.0.1.1

Huawei

Pangu-NLP-N2-128K-5.0.1.1

-

Input tokens/M

-

Output tokens/M

128

Context Length

Pangu-NLP-N2-32K-5.0.1.1

Huawei

Pangu-NLP-N2-32K-5.0.1.1

-

Input tokens/M

-

Output tokens/M

32

Context Length

Pangu-NLP-N2-Reasoner-32K-3.0.1.1

Huawei

Pangu-NLP-N2-Reasoner-32K-3.0.1.1

-

Input tokens/M

-

Output tokens/M

32

Context Length

Pangu-AgentExpert-N1-0.0.2

Huawei

Pangu-AgentExpert-N1-0.0.2

-

Input tokens/M

-

Output tokens/M

32

Context Length

Pangu-NLP-N2-Reasoner-128K-5.0.0.1

Huawei

Pangu-NLP-N2-Reasoner-128K-5.0.0.1

-

Input tokens/M

-

Output tokens/M

128

Context Length

Pangu-NLP-N1-Reasoner-128K-3.0.1.1

Huawei

Pangu-NLP-N1-Reasoner-128K-3.0.1.1

-

Input tokens/M

-

Output tokens/M

128

Context Length

Pangu-NLP-N4-Reasoner-32K-3.0.1.2

Huawei

Pangu-NLP-N4-Reasoner-32K-3.0.1.2

-

Input tokens/M

-

Output tokens/M

32

Context Length

Pangu-NLP-N4-Reasoner-128K-3.0.1.2

Huawei

Pangu-NLP-N4-Reasoner-128K-3.0.1.2

-

Input tokens/M

-

Output tokens/M

128

Context Length

Pangu-AgentExpert-N2-0.0.2

Huawei

Pangu-AgentExpert-N2-0.0.2

-

Input tokens/M

-

Output tokens/M

32

Context Length

Pangu-RAG-N1-32K-4.3.2

Huawei

Pangu-RAG-N1-32K-4.3.2

-

Input tokens/M

-

Output tokens/M

32

Context Length

Pangu-MM-M2-Text2Video-1.0.0

Huawei

Pangu-MM-M2-Text2Video-1.0.0

-

Input tokens/M

-

Output tokens/M

-

Context Length

Pangu-MM-M2-AIGVideo-1.0.0

Huawei

Pangu-MM-M2-AIGVideo-1.0.0

-

Input tokens/M

-

Output tokens/M

-

Context Length

Step-Video-TI2V

Stepfun

Step-Video-TI2V

-

Input tokens/M

-

Output tokens/M

-

Context Length

Pangu-NLP-N4-4K-3.2.36

Huawei

Pangu-NLP-N4-4K-3.2.36

-

Input tokens/M

-

Output tokens/M

4

Context Length

Pangu-NLP-N4-32K-2.5.35

Huawei

Pangu-NLP-N4-32K-2.5.35

-

Input tokens/M

-

Output tokens/M

32

Context Length

Pangu-NLP-N1-128K-3.2.36

Huawei

Pangu-NLP-N1-128K-3.2.36

-

Input tokens/M

-

Output tokens/M

128

Context Length

Pangu-NLP-N2-32K-3.1.35

Huawei

Pangu-NLP-N2-32K-3.1.35

-

Input tokens/M

-

Output tokens/M

32

Context Length

Pangu-NLP-N1-32K-3.2.36

Huawei

Pangu-NLP-N1-32K-3.2.36

-

Input tokens/M

-

Output tokens/M

32

Context Length

Qwen3 Next 80B A3B Instruct 4bit SINQ

huawei-csl

Q

This is a version of the Qwen3-Next-80B large language model after 4-bit quantization using Huawei's SINQ (Sinkhorn Normalized Quantization) method. SINQ is a novel, fast, and high-quality quantization method designed to significantly compress the model size (by approximately 75%) while maintaining almost the same accuracy as the original model, making it easier to deploy.

Natural Language ProcessingSafetensorsSafetensorsEnglish
huawei-csl
304
1

Huawei NoahTinyBERT_General_6L_768_HotpotQA

MarcoYuTono

H

This model is based on the TinyBERT architecture developed by Huawei Noah team, fine-tuned on the HotpotQA dataset, suitable for QA tasks.

Natural Language ProcessingTransformersTransformersEnglish
MarcoYuTono
17
0

Nezha Cn Base

sijunhe

N

NEZHA is a neural contextualized representation model for Chinese understanding, based on the Transformer architecture, developed by Huawei Noah's Ark Lab.

Natural Language ProcessingTransformersTransformers
sijunhe
1.4k
12

TinyBERT_L 4_H 312_v2

nreimers

T

TinyBERT is a lightweight BERT model developed by Huawei Noah's Ark Lab, which compresses the model size through knowledge distillation while maintaining high performance.

Natural Language ProcessingJaxJax
nreimers
5.2k
1
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