natural-language-processing

Environment info

• transformers version: 4.11.2
• Platform: Linux-5.4.0-66-generic-x86_64-with-glibc2.10
• Python version: 3.8.8
• PyTorch version (GPU?): 1.9.1+cu102 (True)
• Tensorflow version (GPU?): not installed (NA)
• F

Change tensor.data to tensor.detach() due to
pytorch/pytorch#6990 (comment)
tensor.detach() is more robust than tensor.data.

In gensim/models/fasttext.py:

    model = FastText(
        vector_size=m.dim,
        vector_size=m.dim,
        window=m.ws,
        window=m.ws,
        epochs=m.epoch,
        epochs=m.epoch,
        negative=m.neg,
        negative=m.neg,
        # FIXME: these next 2 lines read in unsupported FB FT modes (loss=3 softmax or loss=4 onevsall,
        # or model=3 supervi

Is your feature request related to a problem? Please describe.
I typically used compressed datasets (e.g. gzipped) to save disk space. This works fine with AllenNLP during training because I can write my dataset reader to load the compressed data. However, the predict command opens the file and reads lines for the Predictor. This fails when it tries to load data from my compressed files.

Motivated by huggingface/transformers#12789 in Transformers, one welcoming change would be replacing assertions with proper exceptions. The only type of assertions we should keep are those used as sanity checks.

Currently, there is a total of 87 files with the assert statements (located under datasets and src/datasets), so when working on this, to manage the PR s

cf nltk/nltk#2856 (comment)

Hey Hackers of this spoopy month! 👻
Welcome to the Ciphey repo(s)!
This issue requires you to add a decoder.

This wiki section walks you through EVERYTHING you need to know, and we've added some more links at the bottom of this issue to detail more about the decoder.
https://github.com/Ciphey/Ciphey/wiki#adding-your-own-crackers--decoders

https://www.dcode.fr/t9-cipher
https://en.wikipe