Instructions to use kumapo/modernbert-ja-130m-sft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kumapo/modernbert-ja-130m-sft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kumapo/modernbert-ja-130m-sft")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("kumapo/modernbert-ja-130m-sft") model = AutoModelForSequenceClassification.from_pretrained("kumapo/modernbert-ja-130m-sft", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 729f4b16b24503bb73c26083537538159ba3b17dbe0d2abace9b7e15b166d281
- Size of remote file:
- 1.83 MB
- SHA256:
- 008293028e1a9d9a1038d9b63d989a2319797dfeaa03f171093a57b33a3a8277
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