Token Classification
Transformers
ONNX
Safetensors
English
distilbert
resume-parsing
ner
resume
cv
information-extraction
Instructions to use oksomu/resume-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oksomu/resume-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="oksomu/resume-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("oksomu/resume-ner") model = AutoModelForTokenClassification.from_pretrained("oksomu/resume-ner") - Notebooks
- Google Colab
- Kaggle
Somasundaram Ayyappan
Add Kaggle silver training data, retrain model, reorganize data directory
ae7305b - Xet hash:
- 309f4ee55808dcdc1e70a2a98ddc84a1d82c682713ce84c20e7c7ca76bdc210b
- Size of remote file:
- 54.8 MB
- SHA256:
- 905ebc8ef723a3ad1d07e28b26c1bd7e8416896c3570d9dbb30d2b49572cc4d7
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