BERT-SQuAD | SQuAD Question Answering Using BERT, PyTorch | Natural Language Processing library
kandi X-RAY | BERT-SQuAD Summary
kandi X-RAY | BERT-SQuAD Summary
BERT-SQuAD is a Python library typically used in Artificial Intelligence, Natural Language Processing, Deep Learning, Pytorch, Tensorflow, Bert applications. BERT-SQuAD has no bugs, it has no vulnerabilities, it has build file available, it has a Strong Copyleft License and it has low support. You can download it from GitHub.
Stanford Question Answering Dataset (SQuAD) is a reading comprehension dataset, consisting of questions posed by crowdworkers on a set of Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding reading passage, or the question might be unanswerable.
Stanford Question Answering Dataset (SQuAD) is a reading comprehension dataset, consisting of questions posed by crowdworkers on a set of Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding reading passage, or the question might be unanswerable.
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BERT-SQuAD has a low active ecosystem.
It has 371 star(s) with 115 fork(s). There are 7 watchers for this library.
It had no major release in the last 6 months.
There are 8 open issues and 9 have been closed. On average issues are closed in 37 days. There are 1 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of BERT-SQuAD is current.
Quality
BERT-SQuAD has 0 bugs and 0 code smells.
Security
BERT-SQuAD has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
BERT-SQuAD code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
BERT-SQuAD is licensed under the AGPL-3.0 License. This license is Strong Copyleft.
Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.
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BERT-SQuAD releases are not available. You will need to build from source code and install.
Build file is available. You can build the component from source.
Installation instructions, examples and code snippets are available.
BERT-SQuAD saves you 652 person hours of effort in developing the same functionality from scratch.
It has 1513 lines of code, 39 functions and 5 files.
It has high code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed BERT-SQuAD and discovered the below as its top functions. This is intended to give you an instant insight into BERT-SQuAD implemented functionality, and help decide if they suit your requirements.
- Train the model
- Load and cache examples from squad_examples
- Set random seed
- Return the n_best_size of the logits
- Compute softmax
- Convert a list of features to features
- Check if the word spans in the document spans
- Improve the explanation span of an answer span
- Evaluate a model
- Reads a squad example file
- Return the final prediction
- Writes prediction results
- Write prediction results to file
- Predict results
- Convert a squad example to features
- Get an answer for a given example
- Convert a passage to a SquadExample object
- Predict for a passage
- Load and cache examples
Get all kandi verified functions for this library.
BERT-SQuAD Key Features
No Key Features are available at this moment for BERT-SQuAD.
BERT-SQuAD Examples and Code Snippets
No Code Snippets are available at this moment for BERT-SQuAD.
Community Discussions
Trending Discussions on BERT-SQuAD
QUESTION
No such file or directory Error with Google Cloud Storage
Asked 2020-Aug-27 at 01:21
I quite new to Google Cloud Platform and I am trying to train a model with TPU. I follow this tutorial to set up the TPU with Google Colab. All the code below follows the tutorial.
This is the step I have done:
...ANSWER
Answered 2020-Aug-08 at 04:12Can you post the part where run_coqa.py is opening the file?
It seems like you're trying to open it with a regular os. command where you should be using GCP's sdk.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install BERT-SQuAD
unzip and move files to model directory.
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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