Instructions to use jcbao77/sequential_ner_to_nli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jcbao77/sequential_ner_to_nli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="jcbao77/sequential_ner_to_nli")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("jcbao77/sequential_ner_to_nli") model = AutoModelForTokenClassification.from_pretrained("jcbao77/sequential_ner_to_nli") - 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 sha256:19f891157971e11ed4aefacc6a5e1d9ee8c38164a08b678e88020c6b07075be8
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size 430933924
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