Instructions to use bsharpataz/eval_roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bsharpataz/eval_roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="bsharpataz/eval_roberta")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("bsharpataz/eval_roberta") model = AutoModelForTokenClassification.from_pretrained("bsharpataz/eval_roberta") - 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:d2fde8489a92acb2d7dc9ac275b465bbf0cddced75918b7b75a298bf6c939b41
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size 496253316
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