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GloVe | GloVe model for distributed word representation | Natural Language Processing library

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kandi X-RAY | GloVe Summary

GloVe is a C library typically used in Artificial Intelligence, Natural Language Processing, Deep Learning, Bert applications. GloVe has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. You can download it from GitHub.
We provide an implementation of the GloVe model for learning word representations, and describe how to download web-dataset vectors or train your own. See the project page or the paper for more information on glove vectors.

kandi-support Support

  • GloVe has a medium active ecosystem.
  • It has 5544 star(s) with 1331 fork(s). There are 223 watchers for this library.
  • It had no major release in the last 12 months.
  • There are 71 open issues and 71 have been closed. On average issues are closed in 269 days. There are 1 open pull requests and 0 closed requests.
  • It has a neutral sentiment in the developer community.
  • The latest version of GloVe is 1.2

quality kandi Quality

  • GloVe has no bugs reported.

securitySecurity

  • GloVe has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

license License

  • GloVe is licensed under the Apache-2.0 License. This license is Permissive.
  • Permissive licenses have the least restrictions, and you can use them in most projects.

buildReuse

  • GloVe releases are available to install and integrate.
  • Installation instructions, examples and code snippets are available.
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GloVe Key Features

GloVe model for distributed word representation

GloVe Examples and Code Snippets

  • Train word vectors on a new corpus
  • Is storing an object as a value in a key:value pair safe in Python?
  • tf2.0: Gradient Tape returns None gradient in RNN model
  • How does text encoding from tensorflow.keras.preprocessing.text.Tokenizer differ from the old tfds.deprecated.text.TokenTextEncoder
  • Pull out categorical rows and apply to all subsequent rows until new category found
  • How to apply a function for each row in the column python
  • xpath selector returns empty values
  • Validation accuracy is much less than Training accuracy
  • AttributeError: 'Word2Vec' object has no attribute 'most_similar' (Word2Vec)
  • How do I pivot columns?
  • how do you pass text to tensorflow model to return prediction

Train word vectors on a new corpus

$ git clone https://github.com/stanfordnlp/glove
$ cd glove && make
$ ./demo.sh

Community Discussions

Trending Discussions on GloVe
  • Is storing an object as a value in a key:value pair safe in Python?
  • tf2.0: Gradient Tape returns None gradient in RNN model
  • Error while loading vector from Glove in Spacy
  • Difference in hand color between pretrain dataset and fine dataset?
  • How does text encoding from tensorflow.keras.preprocessing.text.Tokenizer differ from the old tfds.deprecated.text.TokenTextEncoder
  • Pull out categorical rows and apply to all subsequent rows until new category found
  • How to apply a function for each row in the column python
  • xpath selector returns empty values
  • Validation accuracy is much less than Training accuracy
  • AttributeError: 'Word2Vec' object has no attribute 'most_similar' (Word2Vec)
Trending Discussions on GloVe

QUESTION

Is storing an object as a value in a key:value pair safe in Python?

Asked 2022-Mar-31 at 04:17

I'm designing the mechanics behind a RPG. There are classes for Item, Player, NPC, etc. The Player class has attributes inventory and equipment. Equipment is a list of dictionaries, such as:

player1.equipment = [{item_slot_a:item_a}, {item_slot_b:item_b}, ..., {item_x:item_x}]

Here, item_slot_a refers to some arbitrary 'item' slot like helmet, boots, gloves, etc., and item_a refers to an instance of the Item class, item1 or something similar. So, notice, the entire object is getting stored as the value of a key:value dictionary pair.

Is this OK?

Is it safe, efficient, and reliable to pass an entire object as a value? I didn't notice this was going to happen until I was testing the player.equip(thing) function. I have a (hopefully) clever way of determining the appropriate equipment slot for equippable items, and then I... well... 'bind' the item to the item slot as a key:value pair. I printed out the inventory to test the equip() function, and saw this:

player1 = create_player('Bob', 'reaver', 1)
player1.show_equipment()
player1.equip(piece_of_gear)
player1.show_equipment()
Output: [{'helmet': None}, {'torso': None}, {'hand': <__main__.Gear object at 0x000001FF200BC0D0>}, {'legs': None}, {'foot': None}, {'neck': None}, {'ring': None}, {'ear': None}, {'charm': None}, {'mh_weapon': None}, {'oh_weapon': None}, {'twohand_weapon': None}]

If I'm correct, this is the print function returning an address in memory denoting the object. Does this represent any issues? I wouldn't normally see this if I were just using the object as a storage mechanism to retrieve relevant values (its intended use), and it's probably just a symptom of me not appropriately designing the show_equipment() function.

Please advise on the structure and reliability of my code, as possible. Any input would be greatly appreciated.

For reference, my player.show_equipment function looks like this:

    print('Equipment:')
    print(self.equipment)
    return\`\`\`

Obviously, if I want to print what's accurately in the equipment list, I could retrieve the object in memory (which will be an instance of the Item class), and print item.name (which is just a string, I wrote it that way) instead of printing the entire item. I'm more curious about the safety and efficacy of creating a list of dictionaries containing objects.

ANSWER

Answered 2022-Mar-31 at 04:17

Is it safe, efficient, and reliable to pass an entire object as a value?

Yes! Everything in Python is an object.

If I'm correct, this is the print function returning an address in memory denoting the object. Does this represent any issues? ... is the print function returning an address in memory denoting the object. Does this represent any issues?

No issues here. It depends entirely on the __repr__ overrides of the class. If it doesn't have one, then the default implementation is to print out the id() of the object and its class type. E.g.

>>> class Test: pass
>>> print(Test())
<__main__.Test object at 0x00000185FF1C5D30>

>>> class Test:
...     def __repr__(self): return "Tada!"

>>> print(Test())
Tada!

Please advise on the structure and reliability of my code, as possible. Any input would be greatly appreciated.

Rather than using an untyped list of dicts as the way to store items, I would instead use a dataclass to represent items. These types classes are the ideal way to store pure data, and implement things like __repr__, __init__ and other useful methods for you! For example:

from dataclasses import dataclass
from typing import Optional


@dataclass
class Gear:
    name: str
    attack_rating: int = 0
    magic_rating: int = 0
    defense_rating: int = 0


@dataclass
class Equipment:
    helmet: Optional[Gear] = None
    torso: Optional[Gear] = None
    hand: Optional[Gear] = None

Using this class you can easily construct your players configuration!

>>> player_equipment = Equipment()
>>> player_equipment.helmet = Gear("Tiara", magic_rating=15)
>>> print(player_equipment)
Equipment(helmet=Gear(name='Tiara', attack_rating=0, magic_rating=15, defense_rating=0), torso=None, hand=None)

Source https://stackoverflow.com/questions/71686734

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install GloVe

The links below contain word vectors obtained from the respective corpora. If you want word vectors trained on massive web datasets, you need only download one of these text files! Pre-trained word vectors are made available under the Public Domain Dedication and License.
Common Crawl (42B tokens, 1.9M vocab, uncased, 300d vectors, 1.75 GB download): glove.42B.300d.zip [mirror]
Common Crawl (840B tokens, 2.2M vocab, cased, 300d vectors, 2.03 GB download): glove.840B.300d.zip [mirror]
Wikipedia 2014 + Gigaword 5 (6B tokens, 400K vocab, uncased, 300d vectors, 822 MB download): glove.6B.zip [mirror]
Twitter (2B tweets, 27B tokens, 1.2M vocab, uncased, 200d vectors, 1.42 GB download): glove.twitter.27B.zip [mirror]

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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