Instructions to use tner/deberta-v3-large-bc5cdr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tner/deberta-v3-large-bc5cdr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="tner/deberta-v3-large-bc5cdr")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("tner/deberta-v3-large-bc5cdr") model = AutoModelForTokenClassification.from_pretrained("tner/deberta-v3-large-bc5cdr") - Notebooks
- Google Colab
- Kaggle
model update
Browse files
README.md
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datasets:
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metrics:
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name: Token Classification
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type: token-classification
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dataset:
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name: bc5cdr
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type: bc5cdr
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args: bc5cdr
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metrics:
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- name: F1
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type: f1
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---
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datasets:
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- tner/bc5cdr
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metrics:
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- f1
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- precision
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name: Token Classification
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type: token-classification
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dataset:
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name: tner/bc5cdr
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type: tner/bc5cdr
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args: tner/bc5cdr
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metrics:
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- name: F1
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type: f1
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