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modelzoo

InfrastructureModel optimizationModel HubPython
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创建于 2022-04-08 · 更新于 2026-10-13 · 今日第 11154 名
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ankitj-cerebrasbhargav-cerebrasshahabn-cerebras

Cerebras/modelzoo 排名第 11,154,有 1,204 个星标。

同类别比较

Cerebras/modelzoo 排名第 11,154,此处有 8 个同类条目;facebookresearch/ToMe 排名第 11,158。

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关键参数与规格
关键参数与规格
参数值
语言Python
类别Infrastructure
子类别Model optimization,Model Hub
关键词Data processing, Distributed training, Inference optimization, Model architecture
星标数1,204
分叉数174
贡献者6
创建日期2022-04-08
更新日期2026-10-13
1 天星标数0
7 天星标数2
排名11,154
上次排名11,103
排名变化-51
7 天星标排名8,168
上次 7 天星标排名10,110
7 天星标排名变化1,942
总星标排名9,667
上次总星标排名9,660
总星标排名变化-7
README 摘录

Cerebras Model Zoo Introduction The Cerebras Model Zoo is a collection of deep learning models and utilities optimized to run on Cerebras hardware. The repository provides reference implementations, configuration files, and utilities that demonstrate best practices for training and deploying models using Cerebras systems. Key Features and Components CLI: The ModelZoo CLI is a comprehensive command-line interface that serves as a single entry point for all ModelZoo-related tasks. It streamlines workflows such as data preprocessing, model training, and

validation. Models: Includes configuration files and reference implementations for a wide range of NLP, vision, and multimodal models, including Llama, Mixtral, DINOv2, and Llava. These are optimized for Cerebras hardware and follow best practices for performance and scalability. Data Preprocessing Tools: Scripts and utilities for preparing datasets for training, including tokenization, formatting, and batching for supported models. Checkpoint Converters and Porting Tools: Tools for converting between checkpoint formats (e. , Cerebras ↔ HuggingFace) and porting PyTorch models to run on Cerebras systems

. Advanced Features: Support for training optimizations such as custom training loops, custom model implementations, µParam (μP) scaling, rotary position embedding (RoPE) scaling for extended sequence lengths, and more. Reach out to us here to get access to Cerebras Hardware and ModelZoo! Install Cerebras ModelZoo by following the steps in our setup guide. Once you have ModelZoo installed, get started by pretraining or finetuning your first model! Visit our developer documentation for comprehensive guides on everything you can do with Cerebras

ModelZoo.

常见问题

记录了多少星标和分叉?

Cerebras/modelzoo 有 1,204 个星标和 174 个分叉。

仓库排名是多少?

Cerebras/modelzoo 排名第 11,154。

记录的语言和类别是什么?

Cerebras/modelzoo 有 1,204 个星标,语言为 Python,类别为 Infrastructure。

哪个仓库排名最接近?

Cerebras/modelzoo 与 facebookresearch/ToMe 比较,后者排名第 11,158,有 1,204 个星标。

README

Cerebras Model Zoo

Introduction

The Cerebras Model Zoo is a collection of deep learning models and utilities optimized to run on Cerebras hardware. The repository provides reference implementations, configuration files, and utilities that demonstrate best practices for training and deploying models using Cerebras systems.

Key Features and Components

  • CLI: The ModelZoo CLI is a comprehensive command-line interface that serves as a single entry point for all ModelZoo-related tasks. It streamlines workflows such as data preprocessing, model training, and validation.
  • Models: Includes configuration files and reference implementations for a wide range of NLP, vision, and multimodal models, including Llama, Mixtral, DINOv2, and Llava. These are optimized for Cerebras hardware and follow best practices for performance and scalability.
  • Data Preprocessing Tools: Scripts and utilities for preparing datasets for training, including tokenization, formatting, and batching for supported models.
  • Checkpoint Converters and Porting Tools: Tools for converting between checkpoint formats (e.g., Cerebras ↔ HuggingFace) and porting PyTorch models to run on Cerebras systems.
  • Advanced Features: Support for training optimizations such as custom training loops, custom model implementations, µParam (μP) scaling, rotary position embedding (RoPE) scaling for extended sequence lengths, and more.

Ready to Get Started?

  • Reach out to us here to get access to Cerebras Hardware and ModelZoo!
  • Install Cerebras ModelZoo by following the steps in our setup guide.
  • Once you have ModelZoo installed, get started by pretraining or finetuning your first model!
  • Visit our developer documentation for comprehensive guides on everything you can do with Cerebras ModelZoo.

Models in this repository

Model Code pointer Model Code pointer
BERT Code BLOOM Code
BTLM Code DiT Code
DINOv2 Code DPO Code
DPR Code ESM-2 Code
Falcon Code Gemma 2 Code
GPT-2 Code GPT-3 Code
GPT-J & GPT-Neox Code Jais Code
LLaMA Code LLaVA Code
Mistral Code Mixtral of Experts Code
Multimodal Simple Code SantaCoder Code
StarCoder Code Transformer Code
T5 Code

License

Apache License 2.0

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