Instructions to use yimiwang/bert-petco-text_content-ctr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yimiwang/bert-petco-text_content-ctr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yimiwang/bert-petco-text_content-ctr")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yimiwang/bert-petco-text_content-ctr") model = AutoModelForSequenceClassification.from_pretrained("yimiwang/bert-petco-text_content-ctr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 46cb0b3c11b012837e3c29f19f5f4e0d3cb5dd39272d8949956b2558341e7996
- Size of remote file:
- 438 MB
- SHA256:
- 5bea3825da89462964e16f56c2586287ec1fa924f392fa94d386de37e394027b
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