Instructions to use delmaksym/aacl22.scale_normformer-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use delmaksym/aacl22.scale_normformer-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="delmaksym/aacl22.scale_normformer-v2")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("delmaksym/aacl22.scale_normformer-v2") model = AutoModel.from_pretrained("delmaksym/aacl22.scale_normformer-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7aff2fe2c03ea498c42764f03d0d9b98d2d87da1de45fed793e5a12c36aabf02
- Size of remote file:
- 504 MB
- SHA256:
- 3cc258f83543c16b7254bf3af5fab5e10742a68c0a10f3544d4385e733dd860c
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