#alibabacloud

[mysocial8onetech]

Learn how Qwen2.5, a large language model developed by Alibaba Cloud, revolutionizes AI with its ability to process long contexts up to 128K tokens and support over 29 languages. Pretrained on a large-scale dataset of 18 trillion tokens, it enhances high-quality code, mathematics, and multilingual data. Discover how it matches Llama-3-405B’s accuracy with only one-fifth of the parameters.

[webartistpro]

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[govindhtech]

Qwen2.5 Coder-32B: Transforming AI Programming Technology

In this blog we discuss Qwen, Qwen2.5, and Qwen2.5 Coder-32B, the cutting-edge AI tool designed to revolutionize programming efficiency, to reach your full development potential.

Introduction Of Qwen

What is Qwen?

Alibaba Cloud has separately built a set of large language models (LLMs) called Qwen. Qwen can provide services and support in a variety of domains and jobs by comprehending and analyzing natural language inputs.

Who made Qwen?

Qwen, created by Alibaba Cloud, advances artificial intelligence (AI) to new heights, making it more intelligent and practical for computer vision, voice comprehension, and natural language processing.

What are the parameters of the Qwen model?

There are four parameter sizes available for the original Qwen model: 1.8B, 7B, 14B, and 72B.

Qwen2 Introduction

Many developers have constructed additional models on top of the Qwen2 language models in the three months after Qwen2 was released, giving us insightful input. Throughout this time, it have concentrated on developing increasingly intelligent and sophisticated language models. To present Qwen2.5, the newest member of the Qwen family.

Dense, user-friendly, decoder-only language models that come in base and instruct variations and sizes of 0.5B, 1.5B, 3B, 7B, 14B, 32B, and 72B.

learned using our most recent large-scale dataset, which contains up to 18 trillion tokens.

notable gains in interpreting structured data (such as tables), producing structured outputs, particularly JSON, following instructions, and producing lengthy texts (more than 8K tokens).

more adaptable to the variety of system prompts, improving chatbot condition-setting and role-play implementation.

Context length is capable of producing up to 8K tokens and supporting up to 128K tokens.

The more than 29 languages supported include Chinese, English, French, Spanish, Portuguese, German, Italian, Russian, Japanese, Korean, Vietnamese, Thai, Arabic, and others.

Qwen2.5 Documentation

Qwen2.5 the following sections make up to documentation:

Quickstart: the fundamental applications and examples;

Inference: the instructions for using transformers for inference, such as batch inference, streaming, etc.

Execute Locally: the guidelines for using frameworks like as llama.cpp and Ollama to execute LLM locally on CPU and GPU;

Deployment: the explanation of how to use frameworks like as vLLM, TGI, and others to deploy Qwen for large-scale inference;

Quantization: the process of using GPTQ and AWQ to quantify LLMs and the instructions for creating high-quality quantized GGUF files;

Training: the post-training guidelines, which include SFT and RLHF (TODO) with Axolotl, LLaMA-Factory, and other frameworks.

Framework: using Qwen in conjunction with application frameworks, such as RAG, Agent, etc.

Benchmark: the memory footprint and inference performance data (available for Qwen2.5).

Qwen2.5 Coder-32B: Overview

The most recent iteration of Code-Specific Qwen big language models, previously known as CodeQwen, is called Qwen2.5-Coder. To satisfy the demands of various developers, Qwen2.5 Coder has so far covered six popular model sizes: 0.5, 1.5, 3, 7, 14, 32 billion parameters. Compared to CodeQwen1.5, Qwen2.5 Coder offers the following enhancements:

Notable advancements in the creation, reasoning, and correction of code. It scale up the training tokens to 5.5 trillion, including source code, text-code grounding, synthetic data, etc., based on the robust Qwen2.5. The most advanced open-source codeLLM at the moment is Qwen2.5 Coder-32B, which can code as well as GPT-4o.

A more thorough basis for practical applications like Code Agents. improving its coding skills while preserving its overall competences and mathematical prowess.

Extended-context Up to 128K tokens are supported.

The instruction-tuned 32B Qwen2.5-Coder model, which is included in this repository, has the following characteristics:

Multiple programming languages.

Training Phase: Pretraining and Posttraining Design: transformers with Attention QKV bias,

RoPE, SwiGLU, and RMSNorm.

There are 32.5 billion parameters.

31.0B is the number of non-embedding parameters.

There are 64 layers.

There are eight Attention Heads (GQA) for KV and forty for Q.

Length of Context: Complete 131,072 tokens.

Code capabilities reaching state of the art for open-source models

Code creation, code reasoning, and code correcting have all seen notable advancements. The 32B model performs competitively with the GPT-4o from OpenAI.

Code Generation: The flagship model of this open-source version, Qwen2.5 Coder 32B Instruct, has outperformed other open-source models on many well-known code generation benchmarks (EvalPlus, LiveCodeBench, and BigCodeBench) and performs competitively with GPT-4o.

Code Repair: One crucial programming ability is code repair. Programming may be made more efficient by using Qwen2.5 Coder 32B Instruct to assist users correct problems in their code. With a score of 73.7, Qwen2.5 Coder 32B Instruct performed similarly to GPT-4o on Aider, a well used benchmark for code correction.

Code reasoning: The term “code reasoning” describes the model’s capacity to comprehend how code is executed and make precise predictions about its inputs and outputs. This 32B model improves upon the remarkable code reasoning performance of the newly published Qwen2.5 Coder 7B Instruct.

Multiple programming languages

All programming languages should be known to an intelligent programming helper. With a score of 65.9 on McEval, Qwen 2.5 Coder 32B excels in over 40 programming languages, with particularly strong performance in Haskell and Racket. During the pre-training stage, the Qwen team used their own special data balancing and cleaning techniques.

Furthermore, Qwen 2.5 Coder 32B Instruct’s multi-language code correction features continue to be excellent, helping users comprehend and alter programming languages they are already acquainted with while drastically lowering the learning curve for new languages. Like McEval, MdEval is a benchmark for multi-language code correction. Qwen 2.5 Coder 32B Instruct ranked top out of all open-source models with a score of 75.2.

Human Preference

Image Credit To Ollama

It created an internal annotated code preference assessment benchmark called Code Arena (which is comparable to Arena Hard) in order to assess how well Qwen 2.5 Coder 32B Instruct aligns with human preferences. Using the “A vs. B win” evaluation approach, which calculates the proportion of test set occurrences where model A’s score is higher than model B’s, it used GPT-4o as the assessment model for preference alignment.

Read more on Govindhtech.com

[bayuhendropurnomo]

Dunia berubah mengikuti perkembangan teknologi yang semakin canggih. Saat ini industri 4.0 dimana semua hal terpaut dengan internet telah menjelma menjadi sebuah kepastian. Generasi baru bahkan telah sejak dini dihadapkan dengan tantangan untuk bersanding dengan teknologi dan internet. Semua aspek kehidupan kini harus memulai menerapkan digitalisasi dan IoT untuk bisa bertahan, mulai dari transportasi, penjual makanan dan minuman, hingga penyedia layanan lain perlu menerapkan digitalisasi agar dilirik dan digunakan oleh society 5.0. Sebagai bagian masa depan dari society 5.0 yang menggunakan teknologi 4.0 maka saya berusaha untuk mengerti dan tidak terjebak sebagai konsumen. Saya ingin menjadi bagian yang mampu untuk mempersiapkan, mengelola dan mampu mengajarkan teknologi 4.0 di dalam kehidupan bermasyarakat.

Dalam industry 4.0 ini talent-talent yang menguasai dunia digital dibutuhkan, dari mulai desig grafis, content creator, platform creator hingga programmer. Salah satu yang terpenting dan yang paling lekat dengan canggihnya teknologi digitalisasi adalah programmer, yang mana ia mengendalikan sebuah platform atau aplikasi untuk bisa beroperasi sesuai dengan yang diharapkan. Untuk bisa mengaktualisasi sebuah program dibutuhkan pemahaman tentang Bahasa program yang biasa di sebut code, dan aktivitasnya disebut Coding. Bahasa pemrograman sendiri ada berbagai macam yang memiliki perbedaannya masing-masing, seperti C++, Java dan sebagainya. Adapun kini, banyak platform yang dikembangkan untuk menjadi pilihan programmer membuat programnya dari mulai yang murni pemrograman, hingga yang applicable dengan berbagai template (hanya tinggal drag n drop saja).

Selain Bahasa pemrograman dan segala platform yang ada, kini muncul pula berbagai layanan cloud sebagai Server virtual yang bisa dimanfaatkan untuk penyimpanan dan sebagai server hosting. Salah satu layanan yang tengah berkembang adalah Alibaba cloud. Alibaba Cloud memiliki berbagai fitur pilihan serta berbagai layanan yang ditawarkan kepada konsumen. Konsepnya Alibaba memiliki bank server yang kemudian ini dibagi-bagi menjadi satuan yang disebut instance. Dalam transaksinya instance ini disewakan kepada konsumen dalam satuan waktu tertentu, mulai dari tiap jam, hari bahkan bulan. Dari model ini, konsumen diuntungkan dengan mendapatkan qualitas baik yang akan dijamin untuk selalu tersedia dan memiliki cost penggunaan yang lebih terjangkau karena konsumen hanya perlu membayar sesuai yang ia pakai. Tidak seperti model konvensional, dimana konsumen harus melakukan maintain atas servernya sendiri yang bisa jadi kapasitasnya tidak di utilisasi sepenuhnya. Sebagai salah satu pionir dalam pengembangan server virtual Alibaba cloud sedang banyak diminati oleh konsumen. Sehingga akan membutuhkan banyak talent yang terampil dalam menangani dan mengelolanya.

Dengan mengikuti program KodeBisat yang diadakan Codepolitan, saya berharap saya dapat memperdalam pemahaman tentang Alibaba Cloud, yang kemudian bisa saya manfaatkan untuk berbagai kepentingan terutama untuk menjadi developer Website dan application. Saya ingin menjadi bagian komunitas orang-orang yang juga ingin menjadi developer handal, sehingga saya dapat menemukan rekan diskusi dan berbagi pengalaman untuk menjadikan wawasan saya semakin luas. Selain itu saya ingin menemukan opportunity baru, dimana saya bisa membantu men-develop website dan applikasi untuk pelaku usaha kecil dan menengah yang mana hingga kini belum tersentuh oleh teknologi. Dengan adanya inisiatif ini saya berharap dapat membantu mereka meningkatkan daya saingnya sehingga bisa bertahan ditengah zaman dengan kemajuan teknologi yang tinggi.

Selain itu saya juga berharap untuk bisa menemukan sumber penghasilan tambahan dengan menjadi developer handal. Saya dengan serius akan mengikuti course yang disediakan oleh Codepolitan dan berharap dapat segera mengimplementasikannya. Ditengah kesibukan saya, saya perlu membagi waktu untuk menyelesaikan kewajiban saya sebagai buruh dan kepala keluarga. Disamping itu, saya akan memanfaatkan waktu pembelajaran ini untuk menjalin banyak relasi dengan rekan seperjuangan nantinya. Saya berharap selepas course ini saya mendapatkan relasi yang memiliki pandangan serupa dan bekerja sama untuk membantu dan mengembangkan pelaku usaha kecil menengah dalam meningkatkan daya saingnya. Terakhir, semoga program ini membawa manfaat dan memberikan barokah kepada semua yang terlibat. Juga agar program ini bisa berjalan dengan baik dan sesuai rencana, sehingga semua pihak akan mendapatkan apa yang diharapkan.

www.Codepolitan.com

www.Alibabacloud.com

www.Devhandal.id

[maximumwobblerbanditdonut]

Gymnastics has evolved so much since Paris 1924.

#paris2024 #ParisGames #olympics #inspiration #alibabacloud #Paris1924 #gymnastics

Posted 10th August 2024

[kanalcoin]

🚀📊 FLock.io Partners with Alibaba Cloud to Revolutionize Decentralized AI! 🤖💥

On a glorious day in April 2025, FLock.io, under the visionary leadership of CEO Jiahao Sun, snagged a game-changing partnership with the tech giant Alibaba Cloud. This isn't just another collab; it's an epic quest towards privacy-first AI powered by the magic of federated learning and blockchain. 📈✨

"Partnering with Alibaba Cloud's Qwen represents a transformative step forward for FLock.io. By leveraging the strengths of blockchain technology and federated learning, we are creating an environment where secure, privacy-preserving model training can drive real-world innovation." — Jiahao Sun, Founder and CEO, FLock.io

This partnership isn’t about just making headlines but signifies a tidal wave of change in how AI models are trained. A few hats are about to be thrown in the air as we challenge current industry standards! 🎩👏

What's the buzz, you wonder? Well, while we may not have all the tea on financials just yet, one thing’s clear: this is a move destined to influence financial and technological outcomes across the crypto landscape. The previous initiatives? Sure, they've been wild, but let’s face it—none carried the sheer scale and potential like this one! 🔥💰

Consider this a Netflix special in the making, filled with high stakes and dramatic twists. Experts are buzzing that by intertwining federated learning with the power of blockchain, we're on the brink of a privacy revolution that could redefine how AI interacts with us. 🌍🛡️

Curious to see how these two titans will reshape the market? Stay plugged into the innovation train! 🚂💨 Follow their journey and keep your investment strategies sharp, because the future of decentralized AI is unwritten, and it's looking bright! For a deeper dive into this groundbreaking partnership, check it out here: Learn more!

Ready to join the conversation? Let us know your thoughts below! ⬇️💬

Disclaimer: This website provides information only and is not financial advice. Cryptocurrency investments are risky. We do not guarantee accuracy and are not liable for losses. Conduct your own research before investing.

#CryptoNews #DecentralizedAI #Blockchain #PrivacyFirst #InvestSmart #FLockIO #AlibabaCloud #CryptoCommunity #FutureTech 🚀✨

[krapalm]

A More Efficient, Innovative and Greener 11.11 Runs Wholly on Alibaba Cloud

A More Efficient, Innovative and Greener 11.11 Runs Wholly on Alibaba Cloud

Global leading cloud provider achieving more with less whilst doubling the use of clean energy at key data centers during the world’s largest global shopping festival Alibaba Cloud, the digital technology and intelligence backbone of Alibaba Group, has once again excelled in its mission of supporting the group’s 11.11 Global Shopping Festival, thanks to its high-performance computing and…

[clunite]

Interested in learning AWS?⠀ ⠀ Top 5 Amazon Web Services or AWS Courses to Learn Online — FREE and Best of Lot⠀ ⠀ https://buff.ly/2QkiWaM⠀ ⠀ ⠀ ⠀ ⠀ #cloud #CloudComputing #cloudsecurity #cloudmarket⠀ ⠀ #google #googlecloudplatform #gcp #gcpcloud⠀ ⠀ #microsoft #azurecloud #Microsoftazure #azure #office365⠀ ⠀ #amazon #aws #AmazonWebServices #awscloud⠀ ⠀ #alibabacloud ⠀ ⠀ #containers #dockers #serverless (at Brampton, Ontario) https://www.instagram.com/p/BsRkm4CBPUI/?utm_source=ig_tumblr_share&igshid=1mfzslr3yw45a

[cloudtechhub]

Alibaba Cloud Firewall achieved Cloud intrusion prevention system (IPS) certification from ICSA Labs, and is the only provider to have passed ICSA Labs' assessment of cloud-native IPS capability in Cloud Firewall. Please feel free to spread this good news:

[creolestudios]

The Initial Steps To Complete The Set-up of Alibaba Cloud

[govindhtech]

PyTorch 2.5: Leveraging Intel AMX For Faster FP16 Inference

Intel Advances AI Development through PyTorch 2.5 Contributions

New features broaden support for Intel GPUs and improve the development experience for AI developers across client and data center hardware.

PyTorch 2.5 supports new Intel data center CPUs. Inference capabilities on Intel Xeon 6 processors are improved by Intel Advanced Matrix Extensions(Intel AMX) for eager mode and TorchInductor, which enable and optimize the FP16 datatype. Windows AI developers can use the TorchInductor C++ backend for a better experience.

Intel Advanced Matrix Extensions(Intel AMX)

Overview of Intel Advanced Matrix Extensions (Intel AMX) to fulfill the computational needs of deep learning workloads, Intel Corporation AMX extends and speeds up AI capabilities. The Intel Xeon Scalable CPUs come with this inbuilt accelerator.

Use Intel AMX to Speed Up AI Workloads

A new built-in accelerator called Intel AMX enhances deep learning training and inference performance on the CPU, making it perfect for tasks like image recognition, recommendation systems, and natural language processing.

What is Intel AMX?

Your AI performance is improved and made simpler using Intel AMX. Designed to meet the computational demands of deep learning applications, it is an integrated accelerator on Intel Xeon Scalable CPUs.

AI Inference Performance Enhancement

Improvement of AI Inference Performance Fourth-generation Intel Xeon Scalable processors with Intel AMX and optimization tools were used by Alibaba Cloud‘s machine learning platform (PAI). When compared to the prior generation, this enhanced end-to-end inferencing.

Optimizing Machine Learning (ML) Models

Improving Models for Machine Learning (ML)Throughput increases using the BERT paradigm over the previous generation were shown by Intel and Tencent using Intel AMX. Tencent lowers total cost of ownership (TCO) and provides better services because to the streamlined BERT model.

Accelerate AI with Intel Advanced Matrix Extensions

Use Intel Advanced Matrix Extensions to Speed Up AI. AI applications benefit from Intel AMX’s performance and power efficiency. It is an integrated accelerator specifically designed for Intel Xeon Scalable CPUs.

PyTorch 2.5

PyTorch 2.5, which was recently published with contributions from Intel, offers artificial intelligence (AI) developers enhanced support for Intel GPUs. Supported GPUs include the Intel Data Center GPU Max Series, Intel Arc discrete graphics, and Intel Core Ultra CPUs with integrated Intel Arc graphics.

These new capabilities provide a uniform developer experience and support, and they aid in accelerating machine learning processes inside the PyTorch community. PyTorch with preview and nightly binary releases for Windows, Linux, and Windows Subsystem for Linux 2 may now be installed directly on Intel Core Ultra AI PCs for researchers and application developers looking to refine, infer, and test PyTorch models.

What is PyTorch 2.5?

A version of the well-known PyTorch open-source machine learning framework is called PyTorch 2.5.

New Featuers of PyTorch 2.5

CuDNN Backend for SDPA: SDPA users with H100s or more recent GPUs may benefit from speedups by default with to the CuDNN Backend for SDPA.

Increased GPU Support: PyTorch 2.5 now supports Intel GPUs and has additional tools to enhance AI programming on client and data center hardware.

Torch Compile Improvements: For a variety of deep learning tasks, Torch.compile has been improved to better inference and training performance.

FP16 Datatype Optimization: Intel Advanced Matrix Extensions for TorchInductor and eager mode enable and optimize the FP16 datatype, improving inference capabilities on the newest Intel data center CPU architectures.

TorchInductor C++ Backend: Now accessible on Windows, the TorchInductor C++ backend improves the user experience for AI developers working in Windows settings.

SYCL Kernels: By improving Aten operator coverage and execution on Intel GPUs, SYCL kernels improve PyTorch eager mode performance.

Binary Releases: PyTorch 2.5 makes it simpler for developers to get started by offering preview and nightly binary releases for Windows, Linux, and Windows Subsystem for Linux 2.Python >= 3.9 and C++ <= 14 are supported by PyTorch 2.5.

Read more on govindhtech.com

[mayovi]

चीन ने शुक्रवार को इस बात से इनकार किया कि वह ई-कॉमर्स दिग्गज Alibaba को कथित तौर पर मोनोपोली नियमों की उल्लंघन के लिए लगभग 1 बिलियन डॉलर का जुर्माना लगाने की योजना बना रहा है। China on Friday denied that it was planning to pay e-commerce giant Alibaba a fine of nearly $1 billion for allegedly violating monopoly rules. #alibaba #alibabacan #alibabagroup #alibabacloud #jackma #jackmaa #jackmaquotes #jackmanews #capitallifestyle #capitalist #capitalista #venturecapitalist #anticapitalist #capitalistcasualties #businessmonopoly #monopoly #monopolymondays #monopolydeal #monopolyman #startupupdates #mayovi #startupnews #china #ecommerce (at India) https://www.instagram.com/p/CMU3zu1H87r/?igshid=1akcdujadnqi8

[webtechexperts]

Alibaba Cloud develops highly scalable cloud and data management service solutions. And as one of its main business group unit, it provides a comprehensive suite of global cloud computing services. In order to power both their international customers’ online businesses and Alibaba Group’s own e-commerce ecosystem. Read and learn more about how #AlibabaCloud works here; https://josephmuciraexclusives.com/what-is-alibaba-cloud/ https://www.instagram.com/p/CEDZ1N6lT3c/?igshid=1nm3ju065mso4

[pullintechnologies]

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