sentencepiece | Unsupervised text tokenizer for Neural Network | Natural Language Processing library
kandi X-RAY | sentencepiece Summary
kandi X-RAY | sentencepiece Summary
Unsupervised text tokenizer for Neural Network-based text generation.
Support
Quality
Security
License
Reuse
Top functions reviewed by kandi - BETA
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of sentencepiece
sentencepiece Key Features
sentencepiece Examples and Code Snippets
Lines of Code : 2License : Strong Copyleft (CC BY-SA 4.0)
Copyner = pipeline("ner", aggregation_strategy="simple", model="dbmdz/bert-large-cased-finetuned-conll03-english") # Named Entity Recognition (NER)
pip install sentencepiece
['1_Pooling', 'config_sentence_transformers.json', 'tokenizer.json', 'tokenizer_config.json', 'modules.json', 'sentence_bert_config.json', 'pytorch_model.bin', 'special_tokens_map.json', 'config.json', 'train_script.py', 'data_config.json'tokenizer = AlbertTokenizer.from_pretrained('albert-base-v2')
pip3 install package_name --user
heroku run bash -a
du -ha --max-depth 1 /app | sort -hr
model = AutoModelForSequenceClassification.from_pretrained(checkpoint, num_labels=1)
model = AutoModelForSequenceClassification.from_pretrained(checkpoint, num_labels=2)
replace_dict = ... # The code below assumes you already have this
no_replace_dict = ...# The code below assumes you already have this
text = ... # The text on input.
def match_fun(match: re.Match):
str_match: str = match.group()
def replace_whole(sentence, replace_token, replace_with, dont_replace):
rx = f"[\"\'\.,:; ]({replace_token})[\"\'\.,:; ]"
iter = re.finditer(rx, sentence)
out_sentence = ""
found = []
indices = []
for m in iter:
class AdamWeightDecayOptimizer(tf.train.Optimizer):
class AdamWeightDecayOptimizer(tf.compat.v1.train.Optimizer):
Community Discussions
Trending Discussions on sentencepiece
QUESTION
I am using the following code
...ANSWER
Answered 2022-Apr-17 at 08:19According to [HuggingFace]: Pipelines - class transformers.TokenClassificationPipeline (emphasis is mine):
- grouped_entities (
bool, optional, defaults to False) - DEPRECATED, useaggregation_strategyinstead. Whether or not to group the tokens corresponding to the same entity together in the predictions or not.
So, your line of code could be:
QUESTION
I've read all of the other questions on this error and frustratingly enough, none give a solution that works.
If I run pip install sentencepiece in the cmd line, it gives me the following output.
ANSWER
Answered 2022-Feb-24 at 15:50I haven't seen this problem in Windows, but for Linux, I would normally reinstall Python after installing the dependencies (such as the MSVC thing). In that case this is especially helpful because I'm often rebuilding (compiling and other related steps) Python/Pip.
Could also just be an error specific to the module and Python version combo you're trying.
From a discussion in the comments:
I have the pyenv-win version manager, so I was able to create venvs and test this for you. With Python 3.10.2, it fails; with Python 3.8.10, it's successful. So, yes, reinstalling does seem to be worthy of your time.
QUESTION
I'm tring to transformer for translation with opennmt-py.
And I already have the tokenizer trained by sentencepiece(unigram).
But I don't know how to use my custom tokenizer in training config yaml.
I'm refering the site of opennmt-docs (https://opennmt.net/OpenNMT-py/examples/Translation.html).
Here are my code and the error .
ANSWER
Answered 2022-Feb-11 at 09:07I got the answers.
- we can use tools/spm_to_vocab in onmt.
- train_from argument is the one.
QUESTION
I have pretrained model for object detection (Google Colab + TensorFlow) inside Google Colab and I run it two-three times per week for new images I have and everything was fine for the last year till this week. Now when I try to run model I have this message:
...ANSWER
Answered 2022-Feb-07 at 09:19It happened the same to me last friday. I think it has something to do with Cuda instalation in Google Colab but I don't know exactly the reason
QUESTION
I have access to the latest packages but I cannot access internet from my python enviroment.
Package versions that I have are as below
...ANSWER
Answered 2022-Jan-19 at 13:27Based on the things you mentioned, I checked the source code of sentence-transformers on Google Colab. After running the model and getting the files, I check the directory and I saw the pytorch_model.bin there.
And according to sentence-transformers code:
Link
the flax_model.msgpack , rust_model.ot, tf_model.h5 are getting ignored when the it is trying to download.
and these are the files that it downloads :
QUESTION
Goal: Amend this Notebook to work with albert-base-v2 model
Error occurs in Section 1.3.
Kernel: conda_pytorch_p36. I did Restart & Run All, and refreshed file view in working directory.
There are 3 listed ways this error can be caused. I'm not sure which my case falls under.
Section 1.3:
...ANSWER
Answered 2022-Jan-14 at 14:09First, I had to pip install sentencepiece.
However, in the same code line, I was getting an error with sentencepiece.
Wrapping str() around both parameters yielded the same Traceback.
QUESTION
Goal: Amend this Notebook to work with albert-base-v2 model.
Kernel: conda_pytorch_p36. I did Restart & Run All, and refreshed file view in working directory.
In order to evaluate and to export this Quantised model, I need to setup a Tokenizer.
Error occurs in Section 1.3.
Both parameters in AutoTokenizer.from_pretrained() throw the same error.
Section 1.3 Code:
...ANSWER
Answered 2022-Jan-14 at 14:07Passing just the model name suffices.
QUESTION
I am trying to install the Tensorflow Object Detection API on a Google Colab and the part that installs the API, shown below, takes a very long time to execute (in excess of one hour) and eventually fails to install.
...ANSWER
Answered 2021-Nov-19 at 00:16I have solved this problem with
QUESTION
I have a requirements.txt file which holds all information of my python packages I need for my Flask application. Here is what I did:
python3 -m venv venvsource venv/bin/activatesudo pip install -r requirements.txt
When I tried to check if the packages were installed on the virtual environment using pip list, I do not see the packages. Can someone tell what went wrong?
ANSWER
Answered 2021-Aug-18 at 18:05If you want to use python3+ to install the packages try to use pip3 install package_name
And to solve the errno 13 try to add --user at the end
QUESTION
I trying to deploy my app to heroku
I have following deploying error
...ANSWER
Answered 2021-Jul-21 at 06:50The maximum allowed slug size is 500MB. Slugs are an important aspect for heroku. When you git push to Heroku, your code is received by the slug compiler which transforms your repository into a slug.
First of all, lets determine what all files are taking up a considerate amount of space in your slug. To do that, fire up your heroku cli and enter / access your dyno by typing the following:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install sentencepiece
cmake
C++11 compiler
gperftools library (optional, 10-40% performance improvement can be obtained.)
You can download and install sentencepiece using the vcpkg dependency manager:. The sentencepiece port in vcpkg is kept up to date by Microsoft team members and community contributors. If the version is out of date, please create an issue or pull request on the vcpkg repository.
Support
Reuse Trending Solutions
Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items
Find more librariesStay Updated
Subscribe to our newsletter for trending solutions and developer bootcamps
Share this Page
