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---
tags:
- spacy
- token-classification
language:
- multilingual
widget:
- text: I'm looking for courses in machine learning.
example_title: Course example
- text: Can you send me some sales jobs?
example_title: Job example
- text: I'm from Berlin, Germany. Can you recommend courses to me?
example_title: Location example
- text: >-
Next month I will be moving to London. I'm looking for software development
jobs there. And can you recommend any language courses so I can meet new
people?
example_title: Mixed example
model-index:
- name: xx_eb_ner
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.99471974
- name: NER Recall
type: recall
value: 0.9937070263
- name: NER F Score
type: f_score
value: 0.9942131253
license: mit
library_name: spacy
---
| Feature | Description |
| --- | --- |
| **Name** | `xx_eb_ner` |
| **Version** | `0.2.0` |
| **spaCy** | `>=3.6.1,<3.7.0` |
| **Default Pipeline** | `tok2vec`, `ner` |
| **Components** | `tok2vec`, `ner` |
| **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
| **Sources** | n/a |
| **License** | mit |
| **Author** | [philipp-zettl](https://huggingface.co/philipp-zettl) |
### Label Scheme
<details>
<summary>View label scheme (3 labels for 1 components)</summary>
| Component | Labels |
| --- | --- |
| **`ner`** | `COURSE_NAME`, `JOB_TITLE`, `LOCATION` |
</details>
### Accuracy
| Type | Score |
| --- | --- |
| `ENTS_F` | 99.54 |
| `ENTS_P` | 99.56 |
| `ENTS_R` | 99.52 |
| `TOK2VEC_LOSS` | 35345.94 |
| `NER_LOSS` | 32265.61 |
### Usage
Install the model via pip:
```shell
pip install https://huggingface.co/philipp-zettl/xx_eb_ner/resolve/main/xx_eb_ner-any-py3-none-any.whl
```
For specific versions, please use the commits provided in the [source repository](https://huggingface.co/philipp-zettl/xx_eb_ner).
Example: version 0.1.0
```shell
pip install https://huggingface.co/philipp-zettl/xx_eb_ner/resolve/c8585148cabcfd04feec0745c17b148a48933f45/xx_eb_ner-any-py3-none-any.whl
```
After installing the model with it's dependencies, you can use it like any other SpaCy model:
```python
# Using spacy.load().
import spacy
nlp = spacy.load("xx_eb_ner")
# Importing as module.
import xx_eb_ner
nlp = xx_eb_ner.load()
```
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