Instructions to use gateswang00/job_ner_skills with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use gateswang00/job_ner_skills with spaCy:
!pip install https://huggingface.co/gateswang00/job_ner_skills/resolve/main/job_ner_skills-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("job_ner_skills") # Importing as module. import job_ner_skills nlp = job_ner_skills.load() - Notebooks
- Google Colab
- Kaggle
Jobs SKILL NER pipeline (spaCy)
Trained spaCy pipeline that labels job-description skills with the
SKILL entity. Consumed by jobs-shared
(jobs_shared.ai.extraction.skill_extractors.ner.NerSkillExtractor).
- Pipeline:
pipelinev0.0.0 - Upstream trainer:
scripts/train/train_ner_skills.pyin jobs-ai-shared (silver labels from cached Vertex extractions filtered through a canon vocabulary). - HF repo:
gateswang00/job_ner_skills
Load locally
import spacy
from huggingface_hub import snapshot_download
local_dir = snapshot_download(repo_id="gateswang00/job_ner_skills")
nlp = spacy.load(local_dir)
doc = nlp("Strong Python and Kubernetes experience required.")
print([(e.text, e.label_) for e in doc.ents])
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