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Merge pull request #2438 from fongjiantan/release/2024.2_AITools
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2024.2 AI Tools Release PR
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jimmytwei authored Aug 7, 2024
2 parents 1895814 + ccc02e9 commit d13605a
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11 changes: 4 additions & 7 deletions AI-and-Analytics/End-to-end-Workloads/Census/sample.json
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"env": [],
"id": "Intel_Modin_E2E_py",
"steps": [
"set -e # Terminate the script on first error",
"source /root/intel/oneapi/intelpython/bin/activate",
"conda create -n modin-hdk python=3.9 -y",
"conda activate modin-hdk",
"source /intel/oneapi/intelpython/bin/activate",
"conda install modin-hdk -c conda-forge -y",
"pip install scikit-learn scikit-learn-intelex matplotlib jupyter ipykernel",
"python -m ipykernel install --name modin-hdk",
"jupyter nbconvert --to notebook --execute census_modin.ipynb"
"pip install scikit-learn scikit-learn-intelex matplotlib",
"pip install jupyter",
"jupyter nbconvert --to notebook census_modin.ipynb"
]
}
]
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Expand Up @@ -111,7 +111,7 @@ This section explains how to train a model for language identification using the

1. Install Jupyter Notebook.
```
conda install jupyter nb_conda_kernels
pip install notebook
```
2. Launch Jupyter Notebook.
```
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1. If you have not already done so, install Jupyter Notebook.
```
conda install jupyter nb_conda_kernels
pip install notebook
```
2. Launch Jupyter Notebook.
```
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"source": [
"from datasets import load_dataset\n",
"\n",
"dataset = load_dataset(\"emotion\", name=\"split\")\n",
"dataset = load_dataset(\"emotion\", name=\"split\", trust_remote_code=True)\n",
"dataset['train'][:10]"
]
},
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Expand Up @@ -49,7 +49,7 @@

from datasets import load_dataset

dataset = load_dataset("emotion", name="split")
dataset = load_dataset("emotion", name="split", trust_remote_code=True)
dataset['train'][:10]


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"linux": [{
"id": "intel amx bf16 int8 inference",
"steps": [
"source /root/intel/oneapi/intelpython/bin/activate",
"source /intel/oneapi/intelpython/bin/activate",
"conda activate pytorch",
"python -m pip install -r requirements.txt",
"python -m ipykernel install --user --name=user_pytorch",
"python -m ipykernel install --user --name=pytorch",
"python pytorch_inference_vnni.py",
"python pytorch_inference_amx.py",
"jupyter nbconvert --ExecutePreprocessor.kernel_name=pytorch --to notebook IntelPyTorch_InferenceOptimizations_AMX_BF16_INT8.ipynb"
"jupyter nbconvert --ExecutePreprocessor.enabled=True --ExecutePreprocessor.kernel_name=pytorch --to notebook IntelPyTorch_InferenceOptimizations_AMX_BF16_INT8.ipynb"
]
}]
},
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@@ -1,4 +1,3 @@
matplotlib
py-cpuinfo
notebook
ipykernel
transformers
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{
"id": "intel amx bf16 training",
"steps": [
"source /root/intel/oneapi/intelpython/bin/activate",
"source /intel/oneapi/intelpython/bin/activate",
"conda activate pytorch",
"python -m pip install -r requirements.txt",
"python -m ipykernel install --user --name=user_pytorch",
"python -m ipykernel install --user --name=pytorch",
"python pytorch_training_avx512_bf16.py",
"python pytorch_training_amx_bf16.py",
"jupyter nbconvert --ExecutePreprocessor.kernel_name=pytorch --to notebook IntelPyTorch_TrainingOptimizations_AMX_BF16.ipynb"
"jupyter nbconvert --ExecutePreprocessor.enabled=True --ExecutePreprocessor.kernel_name=pytorch --to notebook IntelPyTorch_TrainingOptimizations_AMX_BF16.ipynb"
]
}
]
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