Instructions to use jparmet/topic-hf-dropout with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jparmet/topic-hf-dropout with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jparmet/topic-hf-dropout")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jparmet/topic-hf-dropout") model = AutoModelForSequenceClassification.from_pretrained("jparmet/topic-hf-dropout", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7e85325eebc5c1d76a85b9f47384f8fab327d33c07724723c803d64753f5c903
- Size of remote file:
- 670 MB
- SHA256:
- 87740e7a22207d80f9a9a3940b2cb5b270769e4097c7f030214c7716816d955c
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