[1] Install packages

POWERSHELL INSTALL COMMAND

python -m venv c:/ZLAB201/myenv201

C:/ZLAB201/myenv201/Scripts/Activate.ps1

pip install torch==2.1.0+cu121 --index-url https://download.pytorch.org/whl/cu121

pip install numpy==1.26 pandas==2.2.3

pip install ipywidgets

[2] check via python notebook:

check installed packages:

import sys
import os
import numpy

def test_environment():
    print("Testing Virtual Environment: myenv")
    print("Python Executable:", sys.executable)
    print("Python Version:", sys.version)

    # Checking if numpy is installed
    try:
        import numpy as np
        print("NumPy Version:", np.__version__)
    except ImportError:
        print("NumPy is not installed. Installing it now...")
        os.system("pip install numpy")
        import numpy as np
        print("NumPy Version after installation:", np.__version__)

if __name__ == "__main__":
    test_environment()

Output:

Testing Virtual Environment: myenv
Python Executable: c:\ZML1\myenv1\Scripts\python.exe
Python Version: 3.11.9 (tags/v3.11.9:de54cf5, Apr  2 2024, 10:12:12) [MSC v.1938 64 bit (AMD64)]
NumPy Version: 1.26.0

check CUDA:

import torch
print("Torch Version:", torch.__version__)
print("CUDA Available:", torch.cuda.is_available())
print("CUDA Version:", torch.version.cuda)
print("GPU:", torch.cuda.get_device_name(0) if torch.cuda.is_available() else "None")

Output:

Torch Version: 2.1.0+cu121
CUDA Available: True
CUDA Version: 12.1
GPU: NVIDIA GeForce RTX 3050 Ti Laptop GPU

some compatible versions:

Package                   Version
------------------------- --------------
anyio                     4.8.0
argon2-cffi               23.1.0
argon2-cffi-bindings      21.2.0
arrow                     1.3.0
asttokens                 3.0.0
async-lru                 2.0.4
attrs                     25.3.0
babel                     2.17.0
beautifulsoup4            4.13.3
bleach                    6.2.0
certifi                   2025.1.31
cffi                      1.17.1
charset-normalizer        3.4.1
click                     8.1.8
colorama                  0.4.6
comm                      0.2.2
cramjam                   2.9.1
debugpy                   1.8.13
decorator                 5.2.1
defusedxml                0.7.1
emoji                     2.14.1
executing                 2.2.0
fastjsonschema            2.21.1
fastparquet               2024.11.0
fasttext-wheel            0.9.2
filelock                  3.13.1
fqdn                      1.5.1
fsspec                    2024.6.1
gdown                     5.2.0
h11                       0.14.0
httpcore                  1.0.7
httpx                     0.28.1
huggingface-hub           0.29.3
idna                      3.10
ipykernel                 6.29.5
ipython                   9.0.2
ipython_pygments_lexers   1.1.1
ipywidgets                8.1.5
isoduration               20.11.0
jedi                      0.19.2
Jinja2                    3.1.4
joblib                    1.4.2
json5                     0.10.0
jsonpointer               3.0.0
jsonschema                4.23.0
jsonschema-specifications 2024.10.1
jupyter                   1.1.1
jupyter_client            8.6.3
jupyter-console           6.6.3
jupyter_core              5.7.2
jupyter-events            0.12.0
jupyter-lsp               2.2.5
jupyter_server            2.15.0
jupyter_server_terminals  0.5.3
jupyterlab                4.3.5
jupyterlab_pygments       0.3.0
jupyterlab_server         2.27.3
jupyterlab_widgets        3.0.13
MarkupSafe                2.1.5
matplotlib-inline         0.1.7
mistune                   3.1.2
mpmath                    1.3.0
nbclient                  0.10.2
nbconvert                 7.16.6
nbformat                  5.10.4
nest-asyncio              1.6.0
networkx                  3.3
nltk                      3.9.1
notebook                  7.3.2
notebook_shim             0.2.4
numpy                     1.26.0
overrides                 7.7.0
packaging                 24.2
pandas                    2.2.3
pandocfilters             1.5.1
parso                     0.8.4
pillow                    11.1.0
pip                       25.0.1
platformdirs              4.3.6
prometheus_client         0.21.1
prompt_toolkit            3.0.50
psutil                    7.0.0
pure_eval                 0.2.3
pybind11                  2.13.6
pycparser                 2.22
pycryptodomex             3.21.0
Pygments                  2.19.1
PySocks                   1.7.1
python-dateutil           2.9.0.post0
python-json-logger        3.3.0
pytz                      2025.1
pywin32                   309
pywinpty                  2.0.15
PyYAML                    6.0.2
pyzipper                  0.3.6
pyzmq                     26.2.1
referencing               0.36.2
regex                     2024.11.6
requests                  2.32.3
rfc3339-validator         0.1.4
rfc3986-validator         0.1.1
rpds-py                   0.23.1
safetensors               0.5.3
scikit-learn              1.2.2
scipy                     1.15.2
Send2Trash                1.8.3
sentence-transformers     3.4.1
sentencepiece             0.2.0
setuptools                76.0.0
six                       1.17.0
sniffio                   1.3.1
soupsieve                 2.6
stack-data                0.6.3
sympy                     1.13.1
terminado                 0.18.1
threadpoolctl             3.6.0
tinycss2                  1.4.0
tokenizers                0.21.1
torch                     2.1.0+cu121
tornado                   6.4.2
tqdm                      4.67.1
traitlets                 5.14.3
transformers              4.49.0
types-python-dateutil     2.9.0.20241206
typing_extensions         4.12.2
tzdata                    2025.1
uri-template              1.3.0
urllib3                   2.3.0
wcwidth                   0.2.13
webcolors                 24.11.1
webencodings              0.5.1
websocket-client          1.8.0
wheel                     0.45.1
widgetsnbextension        4.0.13

[3] Install transformers

pip install transformers==4.51.3

Run a test code:

from transformers import MobileBertTokenizer, MobileBertModel
import torch

# Use GPU if available
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")

# Load tokenizer and model
tokenizer = MobileBertTokenizer.from_pretrained("google/mobilebert-uncased")
model = MobileBertModel.from_pretrained("google/mobilebert-uncased").to(device)

# Tokenize input
inputs = tokenizer("Hello, MobileBERT!", return_tensors="pt").to(device)

# Run inference
with torch.no_grad():
    outputs = model(**inputs)

# Output shape of last hidden state
print("Last hidden states shape:", outputs.last_hidden_state.shape)

Output:

Last hidden states shape: torch.Size([1, 7, 512])

[4] Duplicate project containing venv scripts

1. In the original project e.g venv200 folder, get the installed package list, store in a subfolder e.g. setup:

   1.    mkdir -p ./setup && pip freeze > ./setup/requirements.txt
      

2. Copy only the project files , not the venv.

3. In the new project folder create a new venv folder, e.g. venv300

   1.  (Assuming that you are already in the venv project root folder, 
        and you have already created requirements.txt file in setup folder)
      
         python -m venv venv300
         ./venv300/Scripts/Activate.ps1
         pip install -r ./setup/requirements.txt
      

4. Note: If your requirements.txt contains CUDA-related packages like the one below, the pip installation will fail. Remove this line from the requirements.txt file before proceeding.

   1. torch==2.1.0+cu121

5. Run the CUDA-related package installation separately in the terminal:

   1. pip install torch==2.1.0+cu121 --index-url https://download.pytorch.org/whl/cu121

6. .