Instructions to use jjzha/jobbert_skill_extraction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jjzha/jobbert_skill_extraction with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="jjzha/jobbert_skill_extraction")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("jjzha/jobbert_skill_extraction") model = AutoModelForTokenClassification.from_pretrained("jjzha/jobbert_skill_extraction") - Notebooks
- Google Colab
- Kaggle
Model for job skills extraction
Hello,
Does anyone know of any models that can extract job skills from ads for electrical engineer, hardware engineer, embedded engineer, for example ads like these:
https://www.linkedin.com/jobs/view/3703707644/
https://www.linkedin.com/jobs/view/3771373721/
https://www.linkedin.com/jobs/view/3732840531/
https://www.linkedin.com/jobs/view/3751616146/
Thnaks in advance
Pavel
You'd want to extract the text from those job openings with a crawler (bs4, scrappy, selenium) and then input the retrieved text into the model.
Which model ?
Well, that depends on your objective. You can use the models uploaded by jjzha to either get the skills or the knowledge of JPs. I suggest using the HF's inference endpoint if you're not that familiar with programming.
I'm familiar with programming and want use model in Python.
Does exist a manual on how to proceed ?