-
Hi, do you have plans to add support for Bayesian filters to spam-detector? The structure of the library and usage looks great, but it'd be far more powerful with more supported spam detectors.
-
- An attacker should take the pre-trained model, original dataset, adversarial dataset (made with transforms), and a list of criteria to monitor (like accuracy, loss, etc) [All the entities in PyTorch…
-
Hello Sir. Are you creating the datasets manually or not ?
Thank you
-
开源先点个赞
但是例子中的aspect_sentiment是不是有误
```
In [8]: my_senta.init_model(model_class="ernie_1.0_skep_large_ch", task="aspect_
...: sentiment_classify", use_cuda=use_cuda)
...: texts = ["百度是一家高科技公…
-
```
Stanford CoreNLP 3.3.1 and above provides a module for sentiment analysis of
sentences. It gives five scores for very negative, negative, neutral, positive,
and very positive (a distribution).
…
-
Just a note in case it's helpful to anyone else - I seemed to be getting 100% accuracy with the on-line sentiment analysis classifier (pages 246-246), but it turned out to be because the code used to …
-
```
Stanford CoreNLP 3.3.1 and above provides a module for sentiment analysis of
sentences. It gives five scores for very negative, negative, neutral, positive,
and very positive (a distribution).
…
-
I tried following the docs for installing and running the program.
At first I tried
```
pip setup.py install
ERROR: unknown command "setup.py"
```
Next I tried
```
python setup.py in…
-
I'm trying to reproduce the example in the README.
```python
name = 'absa/classifier-rest-0.2'
model = absa.BertABSClassifier.from_pretrained(name)
tokenizer = absa.BertTokenizer.from_pretrained…
-
@sheer-coiled has been working on an NLP example: https://github.com/coiled/coiled-examples/blob/sheer_nlp_pipeline_example/nlp-pipeline/nlp_pipline_local_dask_coiled.ipynb
I think we could turn it…