Instructions to use jparmet/pusa-topic-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jparmet/pusa-topic-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jparmet/pusa-topic-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jparmet/pusa-topic-bert") model = AutoModelForSequenceClassification.from_pretrained("jparmet/pusa-topic-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 43077fc461bf23e155c9c8b28490dad679f1a63ca6554bbc7a6c54c8695b4490
- Size of remote file:
- 712 MB
- SHA256:
- a10eb6e5e97791e66a364faf745c03d6ce4006a0ff420917bee598b36bd88c42
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