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<h1 id="intel-gaudi-installation-for-running-ernie-45-series-models">Intel Gaudi Installation for running ERNIE 4.5 Series Models</h1>
<p>The following installation methods are available when your environment meets these requirements:</p>
<ul>
<li>Python 3.10</li>
<li>Intel Gaudi 2</li>
<li>Intel Gaudi software version 1.22.0</li>
<li>Linux X86_64</li>
</ul>
<h2 id="1-run-docker-container">1. Run Docker Container</h2>
<p>Use the following commands to run a Docker container. Make sure to update the versions below as listed in the <a href="https://docs.habana.ai/en/latest/Support_Matrix/Support_Matrix.html">Support Matrix</a>:</p>
<pre><code class="language-console">$ docker pull vault.habana.ai/gaudi-docker/1.22.0/ubuntu22.04/habanalabs/pytorch-installer-2.7.1:latest
$ docker run -it --runtime=habana -e HABANA_VISIBLE_DEVICES=all -e OMPI_MCA_btl_vader_single_copy_mechanism=none --cap-add=sys_nice --net=host --ipc=host vault.habana.ai/gaudi-docker/1.22.0/ubuntu22.04/habanalabs/pytorch-installer-2.7.1:latest
</code></pre>
<h3 id="2-install-paddlepaddle">2. Install PaddlePaddle</h3>
<pre><code class="language-bash">python -m pip install paddlepaddle==3.1.1 -i https://www.paddlepaddle.org.cn/packages/stable/cpu/
</code></pre>
<h3 id="3-install-paddlecustomdevice">3. Install PaddleCustomDevice</h3>
<pre><code class="language-shell">git clone https://github.com/PaddlePaddle/PaddleCustomDevice
cd PaddleCustomDevice/backends/intel_hpu/
mkdir -p build
cd build
cmake ..
make -j
pip install --force-reinstall dist/paddle_intel_hpu*.whl
cd PaddleCustomDevice/backends/intel_hpu/custom_ops
python setup.py install
</code></pre>
<h3 id="4-install-fastdeploy">4. Install FastDeploy</h3>
<pre><code class="language-shell">git clone https://github.com/PaddlePaddle/FastDeploy
cd FastDeploy
bash build.sh
</code></pre>
<h2 id="prepare-the-inference-demo">Prepare the inference demo</h2>
<h3 id="1-start-inference-service">1. Start inference service</h3>
<pre><code class="language-shell">export GC_KERNEL_PATH=/usr/lib/habanalabs/libtpc_kernels.so
export GC_KERNEL_PATH=/usr/local/lib/python3.10/dist-packages/paddle_custom_device/intel_hpu/libcustom_tpc_perf_lib.so:$GC_KERNEL_PATH
export INTEL_HPU_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
export PADDLE_DISTRI_BACKEND=xccl
export PADDLE_XCCL_BACKEND=intel_hpu
export HABANA_PROFILE=0
export HPU_VISIBLE_DEVICES=0
HPU_WARMUP_BUCKET=1 HPU_WARMUP_MODEL_LEN=4096 FD_ATTENTION_BACKEND=HPU_ATTN python -m fastdeploy.entrypoints.openai.api_server --model ERNIE-4.5-21B-A3B-Paddle --tensor-parallel-size 1 --max-model-len 32768 --max-num-seqs 128
</code></pre>
<h3 id="2-launch-the-request">2. Launch the request</h3>
<pre><code class="language-bash">curl -X POST &quot;http://0.0.0.0:8188/v1/chat/completions&quot; \
-H &quot;Content-Type: application/json&quot; \
-d '{
&quot;messages&quot;: [
{&quot;role&quot;: &quot;user&quot;, &quot;content&quot;: &quot;What is AI?&quot;}
], &quot;max_tokens&quot;: 24
}'
</code></pre>
<h3 id="3-successfully-returns-the-result">3. Successfully returns the result</h3>
<pre><code class="language-json">{&quot;id&quot;:&quot;chatcmpl-3bd98ae2-fafe-46ae-a552-d653a8526503&quot;,&quot;object&quot;:&quot;chat.completion&quot;,&quot;created&quot;:1757653575,&quot;model&quot;:&quot;ERNIE-4.5-21B-A3B-Paddle&quot;,&quot;choices&quot;:[{&quot;index&quot;:0,&quot;message&quot;:{&quot;role&quot;:&quot;assistant&quot;,&quot;content&quot;:&quot;**AI (Artificial Intelligence)** refers to the development of computer systems that can perform tasks typically requiring human intelligence.&quot;,&quot;multimodal_content&quot;:null,&quot;reasoning_content&quot;:null,&quot;tool_calls&quot;:null,&quot;prompt_token_ids&quot;:null,&quot;completion_token_ids&quot;:null,&quot;text_after_process&quot;:null,&quot;raw_prediction&quot;:null,&quot;prompt_tokens&quot;:null,&quot;completion_tokens&quot;:null},&quot;logprobs&quot;:null,&quot;finish_reason&quot;:&quot;length&quot;}],&quot;usage&quot;:{&quot;prompt_tokens&quot;:11,&quot;total_tokens&quot;:35,&quot;completion_tokens&quot;:24,&quot;prompt_tokens_details&quot;:{&quot;cached_tokens&quot;:0}}}
</code></pre>
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