Looks like spacy 2.1 --> 2.2 has changed the way lemmatizer objects are built. See stack-overflow answer for details.

I can update the library to account for this migration. I have a fork that I can create a pull request from. Let me know.

Steps to reproduce the behavior:
Run
"fr

As Simple Transformers grows, the single page README documentation has gotten quite bloated and difficult to use. Because of this, I've decided that it's time (if not a little late already) to move the documentation to a more user-friendly Github Pages hosted website at the link below.

https://thilinarajapakse.github.io/simpletransformers/

As of now, only the text classification section is

I did a few training runs of a simple Reformer module with different parameters and logged the GPU memory usage.

Of course, depending on your machine or other things these values can vary, but I thought it might be useful as a visual guide:

dim = 512, seq_len = 256, depth = 1, heads = 1, batch_size = 1: 452 MB

dim = 512, seq_len = 256, depth = 1, heads = 1, batch_size = 8: 992 MB

prediction should include a hyper link to the answer. On clicking the answer from UI will open the pdf page where the answer/paragraph

I have trained almost 80thousand examples within 2000 labels，valid acc almost 92%，but test result all example prob is blew 0.01.
I have tried tranning examples to predict.

The methodology that was outline in the export.md is incredibly out-of-date. TensorFlow has official docker binaries now as well