Basic Tests for testing with natural language processing
Basic Natural language processing tasks using huggingface transformers Inference only
Install required packages for inference
First install miniconda env download at: https://docs.conda.io/en/latest/miniconda.html#linux-installers
bash Miniconda3-py39_4.12.0-Linux-x86_64.sh
GPU
install pytorch
conda install pytorch torchvision torchaudio cudatoolkit=11.6 -c pytorch -c conda-forge
CPU only
conda install pytorch torchvision torchaudio cpuonly -c pytorch
required pip packages
pip install transformers sentencepiece fastapi uvicorn
usage examples, I tested them all in fastapi to speed up the inference without having to load the model again
file-name : program
uvicorn --port 5643 translate-nllb:app
uvicorn --port 5643 translate-mbart-en-pt:app
curl --location --request POST 'http://127.0.0.1:5643/inference' \
--header 'Content-Type: application/json' \
--data-raw '{
"data": {
"prompt": "The quick brown fox jumps over the lazy dog.",
"num_inference_steps": 50,
"scale": "7.5",
"samples": 4
}
}'
Basic Tests for testing with natural language processing
Basic Natural language processing tasks using huggingface transformers Inference only
Install required packages for inference
First install miniconda env download at: https://docs.conda.io/en/latest/miniconda.html#linux-installers
bash Miniconda3-py39_4.12.0-Linux-x86_64.sh
GPU
install pytorch
conda install pytorch torchvision torchaudio cudatoolkit=11.6 -c pytorch -c conda-forge
CPU only
conda install pytorch torchvision torchaudio cpuonly -c pytorch
required pip packages
pip install transformers sentencepiece fastapi uvicorn
usage examples, I tested them all in fastapi to speed up the inference without having to load the model again
file-name : program
uvicorn --port 5643 translate-nllb:app
uvicorn --port 5643 translate-mbart-en-pt:app
curl --location --request POST 'http://127.0.0.1:5643/inference' \
--header 'Content-Type: application/json' \
--data-raw '{
"data": {
"prompt": "The quick brown fox jumps over the lazy dog.",
"num_inference_steps": 50,
"scale": "7.5",
"samples": 4
}
}'