Numpy, BLAS and CUBLAS
In a word: no, you can't do that.
There is a rather good scikit which provides access to CUBLAS from scipy called scikits.cuda which is built on top of PyCUDA. PyCUDA provides a numpy.ndarray like class which seamlessly allows manipulation of numpy arrays in GPU memory with CUDA. So you can use CUBLAS and CUDA with numpy, but you can't just link against CUBLAS and expect it to work.
There is also a commercial library that provides numpy and cublas like functionality and which has a Python interface or bindings, but I will leave it to one of their shills to fill you in on that.
here is another possibility :
http://www.cs.toronto.edu/~tijmen/gnumpy.html
this is basically a gnumpy + cudamat environment which can be used to harness a GPU. also the same code can be run without the gpu using npmat. refer to the link above to download all these files.