MiLM-6B

A large-scale pre-trained language model developed by Xiaomi with a parameter scale of 64 billion.

CommonProductProgrammingNatural Language ProcessingMachine Learning

MiLM-6B, developed by Xiaomi, is a large-scale pre-trained language model with 64 billion parameters. It achieves the best results among models of the same size on the Chinese language benchmark datasets C-Eval and CMMLU. This model represents the latest advancement in the field of natural language processing, possessing strong language comprehension and generation capabilities, and can be widely applied to various scenarios such as text generation, machine translation, and question answering systems.

Supports large-scale parameter training with a parameter scale of 64 billion.
Achieves outstanding results on C-Eval and CMMLU benchmark datasets.
Suitable for various application scenarios such as text generation
machine translation
and question answering systems.
Provides zero-shot and five-shot testing methods.
Model-related information is continuously updated to maintain technological leadership.
Open-source model
facilitating community participation and further development.
Supports operation on various operating systems and hardware platforms.

The MiLM-6B model is suitable for researchers
developers
and enterprise users in the field of natural language processing. Researchers can use it for academic research on language models; developers can develop new applications based on this model; enterprise users can integrate it into their own products to improve the intelligence level of their products.

Used to build intelligent customer service systems
improving customer service efficiency.
Integrated into content recommendation systems to enhance recommendation accuracy.
Applied to machine translation services to enable seamless cross-language communication.

Step 1: Visit the MiLM-6B GitHub page to learn about the basic information of the model.
Step 2: Read the README file to get the installation and configuration guide for the model.
Step 3: Install the necessary dependencies according to the guide and download the model weight files.
Step 4: Configure the model parameters for model training or loading a pre-trained model.
Step 5: Utilize the model for text generation

Visit

MiLM-6B Visit Over Time

Monthly Visits

499904316

Bounce Rate

37.31%

Page per Visit

5.8

Visit Duration

00:06:52

MiLM-6B Visit Trend

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MiLM-6B

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