Instructions to use xt0r3/aihype_incorrectClaimsAboutStudyReport-vs-rest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xt0r3/aihype_incorrectClaimsAboutStudyReport-vs-rest with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xt0r3/aihype_incorrectClaimsAboutStudyReport-vs-rest")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("xt0r3/aihype_incorrectClaimsAboutStudyReport-vs-rest") model = AutoModelForSequenceClassification.from_pretrained("xt0r3/aihype_incorrectClaimsAboutStudyReport-vs-rest", device_map="auto") - 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:ef48cd7fe4bb0871729305990bac99b5abed033e74aaa0c8ec8b793a8ab9ed30
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size 433274956
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