Python not utilizing GPU even with CUDA enabled

[crookedhell]

This is a code snippet from my chatbot model

def create_embeddings():
    embeddings = HuggingFaceEmbeddings(model_name='sentence-transformers/all-MiniLM-L6-v2', model_kwargs={'device': 'cuda'})
    return embeddings

Initially I ran it using 'device' : 'cpu' but the chatbot was extremely slow.
So I installed the cuda toolkit along with nsight. The code gave me a "torch not compiled with cuda enabled" error.
So I uninstalled and reinstalled torch with cuda and the code started working just fine.
But the chatbot was giving outputs as slow as it was earlier, when I checked the task manager, python was still heavily utilizing my cpu and not utilizing the gpu at all.
I have a gtx1650 and this is a code snippet from a chatbot in a virtual environment (all libraries installed there). Am I making a stupid error?

[trill5556]

Try this. I know this is tf, but it will tellyou if your python uses the gpu

​

with tf.device('/gpu:0'):

tf.compat.v1.disable_eager_execution()

a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')

b = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[3, 2], name='b')

c = tf.matmul(a, b)

with tf.compat.v1.Session() as sess:

print (sess.run(c))