Instructions to use upb-nlp/modernbert_fairytaleqa_local_or_sum_attribute with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use upb-nlp/modernbert_fairytaleqa_local_or_sum_attribute with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="upb-nlp/modernbert_fairytaleqa_local_or_sum_attribute")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("upb-nlp/modernbert_fairytaleqa_local_or_sum_attribute") model = AutoModelForSequenceClassification.from_pretrained("upb-nlp/modernbert_fairytaleqa_local_or_sum_attribute", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f8b6782d407f56afc557eb0ffd93ca4fb7861eb6c19b089e180bdf584031dba1
- Size of remote file:
- 5.43 kB
- SHA256:
- 0806b9097b6e2c874a272bb6efedcaa81c335e3c58eaf09be586dfd2812c417f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.