Instructions to use reyvan/bert_large_TruthfulAndSumm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use reyvan/bert_large_TruthfulAndSumm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="reyvan/bert_large_TruthfulAndSumm")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("reyvan/bert_large_TruthfulAndSumm") model = AutoModelForSequenceClassification.from_pretrained("reyvan/bert_large_TruthfulAndSumm", 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:ebeb9b8cb0bb861ae6e34d9f825a88cac1dfb82c489e2a4e5c43df513545b059
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size 1340622760
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