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

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# Grok-1 Inference
An easy-to-use Python + PyTorch + HuggingFace version of 314B Grok-1.
[[code]](https://github.com/hpcaitech/ColossalAI/tree/main/examples/language/grok-1)
[[blog]](https://hpc-ai.com/blog/grok-1-of-pytorch-huggingface-version-is-now-available)
[[HuggingFace Grok-1 PyTorch model weights]](https://huggingface.co/hpcai-tech/grok-1)
## Install
```bash
# 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.
```bash
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:
```bash
./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:
```bash
./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.