Instructions to use jjzha/jobbert_knowledge_extraction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jjzha/jobbert_knowledge_extraction with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="jjzha/jobbert_knowledge_extraction")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("jjzha/jobbert_knowledge_extraction") model = AutoModelForTokenClassification.from_pretrained("jjzha/jobbert_knowledge_extraction") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:ea31238d39c873c67bfc5a99519927e4bea42bd2b037564d40e7bfe5cdefd3ce
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size 430915468
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