Natural language processing

Environment info

• transformers version: 4.11.3
• Platform: Linux-4.19.128-microsoft-standard-x86_64-with-glibc2.2.5
• Python version: 3.8.12
• PyTorch version (GPU?): 1.9.1+cu102 (False)
• Tensorflow version (GPU?): not install

Describe the bug
I'm having major trouble with from_csv.

Context: I'm writing tutorial for build simple text search engine with Jina + Hub. I don't want to include a whole section of processing datasets, hence just passing a CSV into from_csv. I tried with meme dataset (converted tsv) before, and now using [superhero dataset](https://www.kaggle.com/jonathanbesomi/superheroes-nlp-datas

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.

Maybe add something like this as a pre or post processing step?

It might make sense to download the emoji list and store it as part of the build, so people do not need to load the emojis module, ...

import emoji
from emoji import unicode_codes
import re


EMOJI_UNICODE = unicode_codes.EMOJI_UNICODE['en']
emojis = sorted(EMOJI_UNICODE.values(), key=len, reverse=True)
print (emojis