Instructions to use Den4ikAI/ruBert_base_fact_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Den4ikAI/ruBert_base_fact_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Den4ikAI/ruBert_base_fact_detection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Den4ikAI/ruBert_base_fact_detection") model = AutoModelForSequenceClassification.from_pretrained("Den4ikAI/ruBert_base_fact_detection") - Notebooks
- Google Colab
- Kaggle
Commit ·
ef0355a
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Parent(s): 1a13b6e
Adding `safetensors` variant of this model (#2)
Browse files- Adding `safetensors` variant of this model (e887cda9a3468a26cbf2125dc3a4d21446e784a8)
Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:c89ca3c4afa18beaf4f9f18c26352f7d406aaa8be019800891e43444bf646621
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size 711447646
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