Instructions to use mnavas/bertmulti-finetuned-token-reqadjzar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mnavas/bertmulti-finetuned-token-reqadjzar with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mnavas/bertmulti-finetuned-token-reqadjzar")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mnavas/bertmulti-finetuned-token-reqadjzar") model = AutoModelForTokenClassification.from_pretrained("mnavas/bertmulti-finetuned-token-reqadjzar") - 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 sha256:4cf1101be39e528452b9b4c7e4521c0327c192210c0d2a5408701355c7dcd90f
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size 709083980
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