Instructions to use dima806/medium-article-titles-engagement with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dima806/medium-article-titles-engagement with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dima806/medium-article-titles-engagement")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dima806/medium-article-titles-engagement") model = AutoModelForSequenceClassification.from_pretrained("dima806/medium-article-titles-engagement") - Notebooks
- Google Colab
- Kaggle
Commit ·
903c1f1
1
Parent(s): ec15992
Adding `safetensors` variant of this model (#1)
Browse files- Adding `safetensors` variant of this model (422666c35191a0db0420a179588503b116ecd5d7)
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 sha256:394d11cc10bc521f63ad5816c3b250557710698c5e1648bef9cbc3252f734af7
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size 263144680
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