Instructions to use hivaze/ru-e5-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hivaze/ru-e5-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hivaze/ru-e5-large")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hivaze/ru-e5-large") model = AutoModel.from_pretrained("hivaze/ru-e5-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e74f8dce92d178807ddd18a94b462bc8559584cbb8b2fbd3ba2b91e761954ff6
- Size of remote file:
- 1.67 MB
- SHA256:
- 2cfc5d6fdb7fb24dc49542510dcbe39732a39f7e0cbadb53e3704c9dbeba08ca
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