Instructions to use Jsevisal/balanced-augmented-bert-large-gest-pred-seqeval-partialmatch-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jsevisal/balanced-augmented-bert-large-gest-pred-seqeval-partialmatch-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Jsevisal/balanced-augmented-bert-large-gest-pred-seqeval-partialmatch-2")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Jsevisal/balanced-augmented-bert-large-gest-pred-seqeval-partialmatch-2") model = AutoModelForTokenClassification.from_pretrained("Jsevisal/balanced-augmented-bert-large-gest-pred-seqeval-partialmatch-2") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
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version https://git-lfs.github.com/spec/v1
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oid sha256:70137f8589d4ad67bd15e311df028b56880e691a332d5522409b81bc1f0e1b2a
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size 1330341856
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