pip3 install torch==1.0.1 -f https://download.pytorch.org/whl/cpu/stable 
git clone https://github.com/huggingface/torchMoji
import os
os.chdir('torchMoji')
pip3 install -e .
#if you restart the package, the notebook risks to crash on a loop
#I did not restart and worked fine

python3 scripts/download_weights.py

import numpy as np
import emoji, json
from torchmoji.global_variables import PRETRAINED_PATH, VOCAB_PATH
from torchmoji.sentence_tokenizer import SentenceTokenizer
from torchmoji.model_def import torchmoji_emojis
 
EMOJIS = ":joy: :unamused: :weary: :sob: :heart_eyes: :pensive: :ok_hand: :blush: :heart: :smirk: :grin: :notes: :flushed: :100: :sleeping: :relieved: :relaxed: :raised_hands: :two_hearts: :expressionless: :sweat_smile: :pray: :confused: :kissing_heart: :heartbeat: :neutral_face: :information_desk_person: :disappointed: :see_no_evil: :tired_face: :v: :sunglasses: :rage: :thumbsup: :cry: :sleepy: :yum: :triumph: :hand: :mask: :clap: :eyes: :gun: :persevere: :smiling_imp: :sweat: :broken_heart: :yellow_heart: :musical_note: :speak_no_evil: :wink: :skull: :confounded: :smile: :stuck_out_tongue_winking_eye: :angry: :no_good: :muscle: :facepunch: :purple_heart: :sparkling_heart: :blue_heart: :grimacing: :sparkles:".split(' ')
model = torchmoji_emojis(PRETRAINED_PATH)
with open(VOCAB_PATH, 'r') as f:
 vocabulary = json.load(f)
st = SentenceTokenizer(vocabulary, 30)def deepmojify(sentence,top_n =5):
 def top_elements(array, k):
 ind = np.argpartition(array, -k)[-k:]
 return ind[np.argsort(array[ind])][::-1]tokenized, _, _ = st.tokenize_sentences([sentence])
 prob = model(tokenized)[0]
 emoji_ids = top_elements(prob, top_n)
 emojis = map(lambda x: EMOJIS[x], emoji_ids)
 return emoji.emojize(f"{sentence} {' '.join(emojis)}", use_aliases=True)

text = ['I hate coding AI']for _ in text:
 print(deepmojify(_, top_n = 3))

import pandas as pddef emoji_dataset(list1, n_emoji=3):
 emoji_list = [[x] for x in list1]for _ in range(len(list1)):
 for n_emo in range(1, n_emoji+1):
  emoji_list[_].append(deepmojify(list1[_], top_n = n_emoji)[2*-n_emo+1])emoji_list = pd.DataFrame(emoji_list)
 return emoji_listlist1 = ['Stay safe from the virus', 'Push until you break!', 'If it does not challenge you, it will not change you']

emoji_dataset(list1, 5)