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ColossalAI/examples/language/grok-1/README.md

1.5 KiB

Grok-1 Inference

An easy-to-use Python + PyTorch + HuggingFace version of 314B Grok-1. [code] [blog] [HuggingFace Grok-1 PyTorch model weights]

Install

# Make sure you install colossalai from the latest source code
git clone https://github.com/hpcaitech/ColossalAI.git
cd ColossalAI
pip install .
cd examples/language/grok-1
pip install -r requirements.txt

Tokenizer preparation

You should download the tokenizer from the official grok-1 repository.

wget https://github.com/xai-org/grok-1/raw/main/tokenizer.model

Inference

You need 8x A100 80GB or equivalent GPUs to run the inference.

We provide two scripts for inference. run_inference_fast.sh uses tensor parallelism provided by ColossalAI, and it is faster. run_inference_slow.sh uses auto device provided by transformers, and it is slower.

Command format:

./run_inference_fast.sh <model_name_or_path> <tokenizer_path>
./run_inference_slow.sh <model_name_or_path> <tokenizer_path>

model_name_or_path can be a local path or a model name from Hugging Face model hub. We provided weights on model hub, named hpcaitech/grok-1.

Command example:

./run_inference_fast.sh hpcaitech/grok-1 tokenizer.model

It will take 5-10 minutes to load checkpoints. Don't worry, it's not stuck.