Comments (2)
Here is the code:
import spacy
import classy_classification
or import standalon
#from classy_classification import ClassyClassifier
import en_core_web_trf
data = {
"furniture": ["This text is about chairs.",
"Couches, benches and televisions.",
"I really need to get a new sofa."],
"kitchen": ["There also exist things like fridges.",
"I hope to be getting a new stove today.",
"Do you also have some ovens."]
}
nlp = en_core_web_trf.load()
nlp.add_pipe(
"text_categorizer",
config={
"data": data,
"model": "spacy"
}
)
print(nlp("I am looking for kitchen appliances.")._.cats)
from classy-classification.
This was fixed in release 0.6.3 @benhealthee . Thanks for bringing the issue up.
from classy-classification.
Related Issues (20)
- ImportError: cannot import name 'cached_path' from 'transformers.file_utils' (/opt/conda/lib/python3.7/site-packages/transformers/file_utils.py) HOT 3
- Saving and loading models
- retrain on saved pickle model? HOT 2
- add zero-shot `onnx`support
- Misaligned pairings of labels and scores? HOT 8
- add `https://onnx.ai/sklearn-onnx/` support HOT 1
- add saving and loading support for `standalone` reproducability HOT 3
- between zero shot and few shot HOT 1
- setfit in classy classification HOT 7
- Drastic performance drop HOT 5
- Error when using spacy _trf models HOT 6
- Different language models HOT 9
- Standalone usage without spaCy setting embeddings post adding the data makes the classifications run twice HOT 1
- Token indices sequence length HOT 1
- Spacy embeddings vs sentence transformer embeddings HOT 1
- Example code gives error
- Would be great to also apply the classifier on arbitrary Spans HOT 2
- The current version of package is unstable and exceptions occur HOT 2
- Installations on Ubuntu HOT 1
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