Instructions to use mnavas/bert-finetuned-token-reqsolvgencat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mnavas/bert-finetuned-token-reqsolvgencat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mnavas/bert-finetuned-token-reqsolvgencat")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mnavas/bert-finetuned-token-reqsolvgencat") model = AutoModelForTokenClassification.from_pretrained("mnavas/bert-finetuned-token-reqsolvgencat", device_map="auto") - 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 sha256:9a7d4bf1d9bf1941dca40b1d9c99e0ec3d45a6285acd6e0223f2b8c05582982f
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size 709083980
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