Instructions to use MuneK/roberta-base-japanese-finetuned-wrime with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MuneK/roberta-base-japanese-finetuned-wrime with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MuneK/roberta-base-japanese-finetuned-wrime")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MuneK/roberta-base-japanese-finetuned-wrime") model = AutoModelForSequenceClassification.from_pretrained("MuneK/roberta-base-japanese-finetuned-wrime", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1720e39054ecdaf2cd16699e5caf79e4ae27ff2210a79f35eaebf062d8bfad14
- Size of remote file:
- 4.03 kB
- SHA256:
- 6502f4865c66419fc1fddb996137afe40191211a8f4b8819b57fdb669f78e690
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