ipex-llm/python/llm/example/GPU/PyTorch-Models/Model/mamba

Mamba

In this directory, you will find examples on how you could use IPEX-LLM optimize_model API to accelerate Mamba models. For illustration purposes, we utilize the state-spaces/mamba-1.4b and state-spaces/mamba-2.8b as reference Mamba models.

Requirements

To run these examples with IPEX-LLM on Intel GPUs, we have some recommended requirements for your machine, please refer to here for more information.

Example: Predict Tokens using generate() API

In the example generate.py, we show a basic use case for a Mamba model to predict the next N tokens using generate() API, with IPEX-LLM INT4 optimizations on Intel GPUs.

1. Install

We suggest using conda to manage the Python environment. For more information about conda installation, please refer to here.

After installing conda, create a Python environment for IPEX-LLM:

conda create -n llm python=3.9 # recommend to use Python 3.9
conda activate llm

# below command will install intel_extension_for_pytorch==2.0.110+xpu as default
# you can install specific ipex/torch version for your need
pip install --pre --upgrade ipex-llm[xpu] --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/
pip install einops # package required by Mamba

2. Configures OneAPI environment variables

source /opt/intel/oneapi/setvars.sh

3. Run

For optimal performance on Arc, it is recommended to set several environment variables.

export USE_XETLA=OFF
export SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1

python ./generate.py

In the example, several arguments can be passed to satisfy your requirements:

• --repo-id-or-model-path REPO_ID_OR_MODEL_PATH: argument defining the huggingface repo id for the Mamba model (e.g state-spaces/mamba-1.4b and state-spaces/mamba-2.8b) to be downloaded, or the path to the huggingface checkpoint folder. It is default to be state-spaces/mamba-1.4b.
• --tokenizer-repo-id-or-path: argument defining the huggingface repo id for the tokenizer of Mamba model to be downloaded, or the path to the huggingface checkpoint folder. It is default to be EleutherAI/gpt-neox-20b.
• --prompt PROMPT: argument defining the prompt to be infered (with integrated prompt format for chat). It is default to be 'What is AI?'.
• --n-predict N_PREDICT: argument defining the max number of tokens to predict. It is default to be 32.

2.3 Sample Output

state-spaces/mamba-1.4b

Inference time: xxxx s
-------------------- Output --------------------
What is AI?

Artificial Intelligence (AI) is a broad term that describes the use of artificial intelligence (AI) to create artificial intelligence (AI). AI is a

state-spaces/mamba-2.8b

Inference time: xxxx s
-------------------- Output --------------------
What is AI?

Artificial Intelligence is a field of study that focuses on creating machines that can perform intelligent functions. These functions are performed by machines that are smarter than humans