Instructions to use delmaksym/aacl22.scale_pre with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use delmaksym/aacl22.scale_pre with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="delmaksym/aacl22.scale_pre")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("delmaksym/aacl22.scale_pre") model = AutoModel.from_pretrained("delmaksym/aacl22.scale_pre", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cf0d74b92bcfa51bae68b04386a0afff91b0905104117baab0f1d6547c26c3e4
- Size of remote file:
- 504 MB
- SHA256:
- 819b8cf2520b9de89bfef716ad48a5af0bc1053da8438b537f6ddf28fad65c90
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