Instructions to use Nenma/multiconer2-distilbert-test1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nenma/multiconer2-distilbert-test1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Nenma/multiconer2-distilbert-test1")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Nenma/multiconer2-distilbert-test1") model = AutoModelForTokenClassification.from_pretrained("Nenma/multiconer2-distilbert-test1") - 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 sha256:90d0e1165700eb116de31a99e608960d28bbe8a9735f224f3b21034d9f994501
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size 265669964
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