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from tqdm import tqdm
from sentence_transformers import SentenceTransformer, util
from autofaiss import build_index

import sys

spacefile = sys.argv[1]
queryfile = sys.argv[2]

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WARMUP_UPDATES=15000    # Warmup the learning rate over this many updates
TOTAL_UPDATES=5000000    # Total number of training steps

MAX_TOKENS=1024
MAX_POSITIONS=1024       # Num. positional embeddings (usually same as above)
PEAK_LR=[0.0006]          # Peak learning rate, adjust as needed
UPDATE_FREQ=[2]          # Increase the batch size 16x


MODEL=bart_large

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# zsh
sudo apt install zsh
sh -c "$(curl -fsSL https://raw.githubusercontent.com/ohmyzsh/ohmyzsh/master/tools/install.sh)"
echo "exec zsh" >> ~/.bashrc

# zsh-syntax-highlighting
git clone https://github.com/zsh-users/zsh-syntax-highlighting.git
echo "source ${(q-)PWD}/zsh-syntax-highlighting/zsh-syntax-highlighting.zsh" >> ${ZDOTDIR:-$HOME}/.zshrc
source ./zsh-syntax-highlighting/zsh-syntax-highlighting.zsh

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// Unfollow everyone on twitter.com, by Jamie Mason (https://twitter.com/fold_left)
// https://gist.github.com/JamieMason/7580315
//
// 1. Go to https://twitter.com/YOUR_USER_NAME/following
// 2. Open the Developer Console. (COMMAND+ALT+I on Mac)
// 3. Paste this into the Developer Console and run it
//
// Last Updated: 09 April 2020
(() => {
  const $followButtons = '[data-testid$="-unfollow"]';

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import pyautogui
import pyperclip
from time import sleep
import sys

message = f"""Hello

I'm in search of fulltime opportunity at {sys.argv[1]}, could refer me, or pass along my CV to a recruiter?

I'm a graduate student at NYU, currently working at the intersection of Reinforcement Learning and Natural Language Processing, under the supervision of Prof. Yann LeCun.

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def hist(d, count=True):
    import matplotlib.pyplot as plt
    if count:
        d = list(map(len, d))
    n, bins, patches = plt.hist(x=d, bins='auto', color='#0504aa', alpha=0.7, rwidth=0.85)
    plt.grid(axis='y', alpha=0.75)
    plt.xlabel('Value')
    plt.ylabel('Frequency')
    maxfreq = n.max()
    plt.ylim(ymax=np.ceil(maxfreq / 10) * 10 if maxfreq % 10 else maxfreq + 10)

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from torch.optim import Optimizer

class AdamW(Optimizer):
    """
       Implements Adam algorithm with weight decay fix in PyTorch
       Paper: Fixing Weight Decay Regularization in Adam by Ilya Loshchilov, Frank Hutter
       https://arxiv.org/abs/1711.05101
    """
    def __init__(self, params, lr, b1=0.9, b2=0.999, e=1e-8, l2=0,
                 vector_l2=False, max_grad_norm=-1, **kwargs):

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# wordvec_example.py
#
# This file shows one way to work with word2vec data in Python.
#
# Setup:
#
# 1. Install gensim:
#
#     pip install gensim
#

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# wordvec_example.py
#
# This file shows one way to work with word2vec data in Python.
#
# Setup:
#
# 1. Install gensim:
#
#     pip install gensim
#

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