[Solved] Which Python code snippet correctly loads GloVe embeddings from a text file into a dictionary? — Ans: with open('glove.txt') as f: embeddings = {line.split()[0]: list(map(float,... | NLP

NLP - Word Embeddings

Which Python code snippet correctly loads GloVe embeddings from a text file into a dictionary?

Awith open('glove.txt') as f: embeddings = {line.split()[0]: list(map(float, line.split()[1:])) for line in f}

Bwith open('glove.txt') as f: embeddings = {line[0]: line[1:] for line in f.read().split()}

Cembeddings = open('glove.txt').readlines().split()

Dembeddings = dict(open('glove.txt').read())

Step-by-Step Solution

Solution:

Step 1: Understand GloVe file format
Each line has a word followed by numbers representing its vector.
Step 2: Check code correctness
with open('glove.txt') as f: embeddings = {line.split()[0]: list(map(float, line.split()[1:])) for line in f} splits each line, uses first token as key, rest as float vector list, which is correct.
Final Answer:
with open('glove.txt') as f: embeddings = {line.split()[0]: list(map(float, line.split()[1:])) for line in f} -> Option A
Quick Check:
Correct loading = split line, map floats, assign word key [OK]

Quick Trick: Split line, first word key, rest floats vector [OK]

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