- A series of transformer models that embed your course documents, search for them when you ask it a question, and construct a reply in coherent english using a text2text generator.
- Based on the work done by deepset.ai in their Haystack library.
- As the notebook preview does not always load on GitHub, click here for the Colab notebook / demo. Instructions are provided on what to edit to use the notebook both in simple cases (i.e. just changing the questions) to adapting the notebook for other purposes.
question to model: What is the k-means algorithm?
model response:
("'the k means algorithm is one of the most popular iterative descent clustering methods intended for situations in which all variables are of the quantitative type, and that for each such assignment there is a unique optimum for the k pk, the algorithm must converge after a finite number of iterations. it is not clear that the hard assignment to the nearest cluster is the most appropriate. since the assignment of observations to clusters at any iteration is a perturbation of that for the previous iteration, only a very small fraction of all possible assignments. however, these algorithms converge to local optima which may be highly suboptimal when compared to the global optimum. in the present invention, the convergence properties of these algorithms are studied and it is shown that if the algorithm converges to a local maximum of l, this will correspond to a global maximum of the log likelihood function; and so in this incremental algorithm is increasing the value of l and if the result no longer changes, a local optimum has been reached.'")
