Instructions to use nikchar/claim_detection_roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nikchar/claim_detection_roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nikchar/claim_detection_roberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nikchar/claim_detection_roberta") model = AutoModelForSequenceClassification.from_pretrained("nikchar/claim_detection_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 sha256:290aa28b0215e0784f68dd05ab963684cc45ddb4bcbe48586fb42580a018942d
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size 498612824
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