Instructions to use cbruinsm/en_Coff_Ev1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use cbruinsm/en_Coff_Ev1 with spaCy:
!pip install https://huggingface.co/cbruinsm/en_Coff_Ev1/resolve/main/en_Coff_Ev1-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("en_Coff_Ev1") # Importing as module. import en_Coff_Ev1 nlp = en_Coff_Ev1.load() - Notebooks
- Google Colab
- Kaggle
Your Coffee Ordered at the Speed of Sound
For citations please use the included refs.bib this project was a collaboration between five students with a common goal of simplifying the ordering process.
You are permitted to use this software for any projects, however this is not permitted for use in any commerical instances under our cc-by-nc-sa-3.0
license without explicit permissions from the author(s).
| Feature | Description |
|---|---|
| Name | en_Coff_Ev1 |
| Version | 1.4.0 |
| spaCy | >=3.4.3,<3.5.0 |
| Default Pipeline | tok2vec, ner |
| Components | tok2vec, ner |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | n/a |
| License | cc-by-nc-sa-3.0 |
| Author | C.Bruinsma,I.Chi,J.Feliciano,J.Li,D.Paden |
THIS SOFTWARE IS PROVIDED AS IS BY ITS AUTHORS UNDER NO WARRANTY OF ITS FUNCTION.
Label Scheme
View label scheme (20 labels for 1 components)
| Component | Labels |
|---|---|
ner |
Anti, Blended, Brew Style, Coffee Varietal, add-on, drink, extra, hot breakfast, milk, milk texture, pastry, pump quantity, roast, shot quality, shot quantity, size, syrup, temperature, toppings, upside-down |
Accuracy
| Type | Score |
|---|---|
ENTS_F |
97.72 |
ENTS_P |
96.73 |
ENTS_R |
98.73 |
TOK2VEC_LOSS |
54858.85 |
NER_LOSS |
427986.33 |
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Evaluation results
- NER Precisionself-reported0.967
- NER Recallself-reported0.987
- NER F Scoreself-reported0.977