Instructions to use shamz15531/roberta_tuple_matcher_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shamz15531/roberta_tuple_matcher_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="shamz15531/roberta_tuple_matcher_base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("shamz15531/roberta_tuple_matcher_base") model = AutoModelForSequenceClassification.from_pretrained("shamz15531/roberta_tuple_matcher_base") - 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 sha256:26ecc6971269da344714ec61e20fbb35445a9f744459424985cf7d6e4a12ac3d
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size 498626240
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