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r200_8f_xtrt_llm/examples/gptj/README.md
2025-08-06 15:49:14 +08:00

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# GPT-J
This document explains how to build the [GPT-J](https://huggingface.co/EleutherAI/gpt-j-6b) model using XTRT-LLM and run on a single XPU.
## Overview
The XTRT-LLM GPT-J example
code is located in [`examples/gptj`](./). There are several main files in that folder:
* [`build.py`](./build.py) to build the [XTRT] engine(s) needed to run the GPT-J model,
* [`run.py`](./run.py) to run the inference on an input text,
## Support Matrix
* FP16
## Usage
### 1. Download weights from HuggingFace (HF) Transformers
```bash
# 1. Weights & config
git clone https://huggingface.co/EleutherAI/gpt-j-6b ./downloads/gptj-6b
pushd ./downloads/gptj-6b && \
rm -f pytorch_model.bin && \
wget https://huggingface.co/EleutherAI/gpt-j-6b/resolve/main/pytorch_model.bin && \
popd
# 2. Vocab and merge table
wget https://huggingface.co/EleutherAI/gpt-j-6b/resolve/main/vocab.json
wget https://huggingface.co/EleutherAI/gpt-j-6b/resolve/main/merges.txt
```
### 2. Build XTRT engine(s)
XTRT-LLM builds XTRT engine(s) using a HF checkpoint. If no checkpoint directory is specified, XTRT-LLM will build engine(s) using
dummy weights.
Examples of build invocations:
```bash
# Build a float16 engine using HF weights.
# Enable several XTRT-LLM plugins to increase runtime performance. It also helps with build time.
python3 build.py --dtype=float16 \
--log_level=verbose \
--enable_context_fmha \
--use_gpt_attention_plugin float16 \
--use_gemm_plugin float16 \
--max_batch_size=32 \
--max_input_len=1919 \
--max_output_len=128 \
--output_dir=./downloads/gptj-6b/trt_engines/fp16/1-XPU/ \
--model_dir=./downloads/gptj-6b 2>&1 | tee build.log
# Build a float16 engine using dummy weights, useful for performance tests.
# Enable several XTRT-LLM plugins to increase runtime performance. It also helps with build time.
python3 build.py --dtype=float16 \
--log_level=verbose \
--enable_context_fmha \
--use_gpt_attention_plugin float16 \
--use_gemm_plugin float16 \
--max_batch_size=32 \
--max_input_len=1919 \
--max_output_len=128 \
--output_dir=./downloads/gptj-6b/trt_engines/gptj_engine_dummy_weights 2>&1 | tee build.log
```
### 3. Run
To run a XTRT-LLM GPT-J model:
```bash
python3 run.py --max_output_len=50 \
--engine_dir=./downloads/gptj-6b/trt_engines/fp16/1-XPU/ \
--hf_model_location=./downloads/gptj-6b
```