Instructions to use Jsevisal/balanced-augmented-ft-bert-large-gest-pred-seqeval-partialmatch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jsevisal/balanced-augmented-ft-bert-large-gest-pred-seqeval-partialmatch with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Jsevisal/balanced-augmented-ft-bert-large-gest-pred-seqeval-partialmatch")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Jsevisal/balanced-augmented-ft-bert-large-gest-pred-seqeval-partialmatch") model = AutoModelForTokenClassification.from_pretrained("Jsevisal/balanced-augmented-ft-bert-large-gest-pred-seqeval-partialmatch", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#2)
Verified signature- Adding `safetensors` variant of this model (c321053495cba88a3e39a881a3adf4fd2a12ec78) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>dbc2283
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Create README.md
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initial commit
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