Instructions to use nhanv/ner_cv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nhanv/ner_cv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="nhanv/ner_cv")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("nhanv/ner_cv") model = AutoModelForTokenClassification.from_pretrained("nhanv/ner_cv") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
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 sha256:5d7a0afdf75257562825af91d466d6f1f812ab6dfcef33ed4852d14aa05d4db4
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size 735474748
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