Instructions to use shengqin/bert-seq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shengqin/bert-seq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="shengqin/bert-seq")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("shengqin/bert-seq") model = AutoModelForSequenceClassification.from_pretrained("shengqin/bert-seq", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 82e42abba4b811ef33c2982cc7612fb021be0756eb12402139f6b17f62543386
- Size of remote file:
- 4.03 kB
- SHA256:
- 8415adab7e84914f389d8140f1e1296abcf47503755409624028382defb78d50
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