rwkv 7 world

Introduction

RWKV-7 WORLD is a language model designed for text generation tasks, supporting 12 different languages. It is built using PyTorch and follows the causal language modeling architecture. The model is trained on an extensive dataset comprising over 3.1 trillion tokens, with a significant focus on English, multilingual content, and code.

Architecture

RWKV-7 utilizes the causal language model (causal-lm) architecture, a common approach in generative models that predicts the next token in a sequence based on previous tokens. The model is implemented with the PyTorch library, ensuring compatibility with various deep learning frameworks.

Training

The model was trained on diverse datasets, including HuggingFaceFW/fineweb-edu, mlfoundations/dclm-baseline-1.0, cerebras/SlimPajama-627B, EleutherAI/pile, bigcode/starcoderdata, and oscar-corpus/OSCAR-2301. The training data consists of over 3.1 trillion tokens, with training iterations named World-v3, World-v2.9, and World-v2.8, indicating the amount of data used.

Guide: Running Locally

To run RWKV-7 WORLD locally:

1. Install the RWKV pip package:
   Install version 0.8.28 or later using pip install rwkv.

2. Access the repository:
   Visit the RWKV GitHub repository for developer resources and guidance.

3. Run the Chat Demo:
   Utilize the ChatRWKV demo script to see an example of the model in action.

4. Cloud GPU recommendation:
   Consider using cloud services like AWS, Google Cloud, or Azure for GPU support to enhance performance during inference.

License

RWKV-7 WORLD is released under the Apache 2.0 license, allowing for broad use and distribution with proper attribution.