BERT

BERT

Google
CodeQwen

CodeQwen

Alibaba
+
+

Related Products

  • Gemini Enterprise Agent Platform
    999 Ratings
    Visit Website
  • Google AI Studio
    40 Ratings
    Visit Website
  • LM-Kit.NET
    29 Ratings
    Visit Website
  • kama.ai
    9 Ratings
    Visit Website
  • Planview AdaptiveWork
    714 Ratings
    Visit Website
  • Concord
    237 Ratings
    Visit Website
  • Adobe Firefly
    25,030 Ratings
    Visit Website
  • iTacit
    46 Ratings
    Visit Website
  • ClickLearn
    67 Ratings
    Visit Website
  • Google Cloud BigQuery
    2,027 Ratings
    Visit Website

About

BERT is a large language model and a method of pre-training language representations. Pre-training refers to how BERT is first trained on a large source of text, such as Wikipedia. You can then apply the training results to other Natural Language Processing (NLP) tasks, such as question answering and sentiment analysis. With BERT and AI Platform Training, you can train a variety of NLP models in about 30 minutes.

About

CodeQwen is the code version of Qwen, the large language model series developed by the Qwen team, Alibaba Cloud. It is a transformer-based decoder-only language model pre-trained on a large amount of data of codes. Strong code generation capabilities and competitive performance across a series of benchmarks. Supporting long context understanding and generation with the context length of 64K tokens. CodeQwen supports 92 coding languages and provides excellent performance in text-to-SQL, bug fixes, etc. You can just write several lines of code with transformers to chat with CodeQwen. Essentially, we build the tokenizer and the model from pre-trained methods, and we use the generate method to perform chatting with the help of the chat template provided by the tokenizer. We apply the ChatML template for chat models following our previous practice. The model completes the code snippets according to the given prompts, without any additional formatting.

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

Developers interested in a powerful large language model

Audience

Anyone seeking an AI tool to improve their natural language understanding operations and text generation tasks

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Not Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Not Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version Supported
Free Trial Not Supported

Pricing

Free
Free Version Supported
Free Trial Not Supported

Reviews/Ratings

Overall 4.0 / 5
ease 4.0 / 5
features 4.0 / 5
design 3.0 / 5
support 3.0 / 5

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

Pros & Cons from Real Users

Pros

  • When BERT model implemented on stress detection use case, BERT as it handles context of the text was easily able to identify negation sentence like detecting "I am NOT happy" as a stressful text which was not happening in other models like logistic regression, decision tree, random forest, multinomial naive bayes, CNN, RNN, LSTM etc.

Cons

  • difficulty in finding a suitable multilingual datastet to train the model for both hind and english use cases.

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Supported
In Person Not Supported

Company Information

Google
Founded: 1998
United States
cloud.google.com/ai-platform/training/docs/algorithms/bert-start

Company Information

Alibaba
Founded: 1999
China
github.com/QwenLM/CodeQwen1.5

Alternatives

Gemini

Gemini

Google

Alternatives

CodeGemma

CodeGemma

Google
ALBERT

ALBERT

Google
Qwen-7B

Qwen-7B

Alibaba
BLOOM

BLOOM

BigScience
Qwen2.5-Max

Qwen2.5-Max

Alibaba
RoBERTa

RoBERTa

Meta
Qwen2

Qwen2

Alibaba
GPT-4

GPT-4

OpenAI
Qwen 4

Qwen 4

Alibaba

Categories

Categories

Integrations

AWS Marketplace Supported
Alibaba Cloud Not Supported
Alpaca Supported
Amazon SageMaker Model Training Supported
Code Llama Not Supported
Codeforces Not Supported
Conda Not Supported
GPT-4 Not Supported
Gopher Supported
Hugging Face Not Supported
LangChain Not Supported
LlamaIndex Not Supported
ModelScope Not Supported
Ollama Not Supported
PostgresML Supported
PyTorch Not Supported
Python Not Supported
Qwen Studio Not Supported
Spark NLP Supported
StarCoder Not Supported

Integrations

AWS Marketplace Not Supported
Alibaba Cloud Supported
Alpaca Not Supported
Amazon SageMaker Model Training Not Supported
Code Llama Supported
Codeforces Supported
Conda Supported
GPT-4 Supported
Gopher Not Supported
Hugging Face Supported
LangChain Supported
LlamaIndex Supported
ModelScope Supported
Ollama Supported
PostgresML Not Supported
PyTorch Supported
Python Supported
Qwen Studio Supported
Spark NLP Not Supported
StarCoder Supported
Claim BERT and update features and information
Claim BERT and update features and information
Claim CodeQwen and update features and information
Claim CodeQwen and update features and information