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# BERT (language model) is selected on hands-on section | ||
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Bidirectional Encoder Representations from Transformers (BERT) is a transformer-based machine learning technique for natural language processing (NLP) pre-training developed by Google. | ||
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# SambaNova | ||
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1. Login to SN: | ||
``` | ||
ssh [email protected] | ||
ssh sm-01 (or sm-02) | ||
``` | ||
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2. SDK setup: | ||
``` | ||
source /software/sambanova/envs/sn_env.sh | ||
``` | ||
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3. Copy scripts: | ||
``` | ||
cp /var/tmp/Additional/slurm/Models/ANL_Acceptance_RC1_11_5/bert_train-inf.sh ~/ | ||
``` | ||
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4. Run scripts: | ||
``` | ||
cd ~ | ||
./bert_train-inf.sh | ||
``` | ||
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# Cerebras | ||
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1. Login to CS-2: | ||
``` | ||
ssh [email protected] | ||
ssh cs2-01-med1 | ||
``` | ||
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2. Copy scripts: | ||
``` | ||
cp -r /software/cerebras/model_zoo ~/ | ||
cd model_zoo/modelzoo/transformers/tf/bert | ||
``` | ||
Ignore any permissions errors during the copy of the subdirectory `modelzoo-R1.3.0_2/`. | ||
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Next, modify `data_dir` to `'/software/cerebras/dataset/bert_large/msl128/'` in `configs/params_bert_large_msl128.yaml`, **in two places**. | ||
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4. Run scripts: | ||
``` | ||
MODELDIR=model_dir_bert_large_msl128_$(hostname) | ||
rm -r $MODELDIR | ||
time -p csrun_cpu python run.py --mode=train --compile_only --params configs/params_bert_large_msl128.yaml --model_dir $MODELDIR --cs_ip $CS_IP | ||
time -p csrun_wse python run.py --mode=train --params configs/params_bert_large_msl128.yaml --model_dir $MODELDIR --cs_ip $CS_IP | ||
``` | ||
# Introduction to AI Testbeds at ALCF and hands | ||
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Please refer to [Slides here](./AI%20Testbeds%20Hands-on%20ATPESC2023.pdf) and [online documentation](https://docs.alcf.anl.gov/ai-testbed/getting-started/) |