Instructions to use Vikhrmodels/vikhr_encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vikhrmodels/vikhr_encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Vikhrmodels/vikhr_encoder")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Vikhrmodels/vikhr_encoder") model = AutoModel.from_pretrained("Vikhrmodels/vikhr_encoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 73e27d7b298a04bd1b2378eb61599ec6481b703f594bd0942c7e3f004749fe52
- Size of remote file:
- 1.64 MB
- SHA256:
- e3f0f84b42f79947ab92931c7c5ded699e845e6862e4e29f0b97f87e279da601
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