Caver | Caver : a toolkit for multilabel text classification | Machine Learning library
kandi X-RAY | Caver Summary
kandi X-RAY | Caver Summary
Caver is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. Caver 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 install using 'pip install Caver' or download it from GitHub, PyPI.
Rising a torch in the cave to see the words on the wall, tag your short text in 3 lines. Caver uses Facebook's PyTorch project to make the implementation easier. Demo • Requirements • Install • Pre-trained models • Train • Examples • Document.
Rising a torch in the cave to see the words on the wall, tag your short text in 3 lines. Caver uses Facebook's PyTorch project to make the implementation easier. Demo • Requirements • Install • Pre-trained models • Train • Examples • Document.
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Quality
Security
License
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Caver has a low active ecosystem.
It has 37 star(s) with 2 fork(s). There are 9 watchers for this library.
It had no major release in the last 12 months.
There are 0 open issues and 2 have been closed. On average issues are closed in 4 days. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of Caver is 0.2
Quality
Caver has 0 bugs and 0 code smells.
Security
Caver has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
Caver code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
Caver is licensed under the GPL-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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Caver releases are available to install and integrate.
Deployable package is available in PyPI.
Build file is available. You can build the component from source.
Installation instructions are not available. Examples and code snippets are available.
Caver saves you 490 person hours of effort in developing the same functionality from scratch.
It has 1153 lines of code, 78 functions and 23 files.
It has medium code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed Caver and discovered the below as its top functions. This is intended to give you an instant insight into Caver implemented functionality, and help decide if they suit your requirements.
- Train the model
- Evaluate the model
- Train a single step
- Compute the f - score between precision and recall scores
- Process training data
- Check command line arguments
- Compute the evaluation of the prediction
- Loads checkpoint from file
- Return the top label of the given text
- Predict logits
- Cut text
- Predict the label of the model
- Get model output
- Forward pass through the input sequence
- Predict the labels for the given batch
- Calculate the prediction probability of the model
- Compute the inner layer
- Compute the attention layer
- Calculate the probability of the model
- Predict labels for a given character
- Predict the best prediction
- Predict the predictions from the given text
Get all kandi verified functions for this library.
Caver Key Features
No Key Features are available at this moment for Caver.
Caver Examples and Code Snippets
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from caver import CaverModel
model = CaverModel("./checkpoint_path")
sentence = ["看 美 剧 学 英 语 靠 谱 吗",
"科 比 携 手 姚 明 出 任 2019 篮 球 世 界 杯 全 球 大 使",
"如 何 在 《 权 力 的 游 戏 》 中 苟 到 最 后",
"英 雄 联 盟 LPL 夏 季 赛 RNG 能 否 击 败 TOP 战
Copy
$ python3 train.py --input_data_dir {path to your origin dataset}
--output_data_dir {path to store the preprocessed dataset}
--train_filename train.tsv
--valid_filename valid.tsv
Copy
$ wget -O - https://github.com/guokr/Caver/releases/download/0.1/checkpoints_char_cnn.tar.gz | tar zxvf -
$ wget -O - https://github.com/guokr/Caver/releases/download/0.1/checkpoints_char_lstm.tar.gz | tar zxvf -
Community Discussions
Trending Discussions on Caver
QUESTION
Pandas Merge Not Working When Values Are an Exact Match
Asked 2022-Apr-01 at 20:33
Below is my code and Dataframes. stats_df
is much bigger. Not sure if it matters, but the column values are EXACTLY as they appear in the actual files. I can't merge the two DFs without losing 'Alex Len' even though both DFs have the same PlayerID value of '20000852'
ANSWER
Answered 2022-Apr-01 at 20:33You need to specify the column you want to merge on using the on
keyword argument:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install Caver
You can install using 'pip install Caver' or download it from GitHub, PyPI.
You can use Caver like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
You can use Caver like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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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