Instructions to use deepvk/bert-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepvk/bert-base-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="deepvk/bert-base-uncased")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("deepvk/bert-base-uncased") model = AutoModel.from_pretrained("deepvk/bert-base-uncased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from deepvk/bert-base-uncased: direct link, hf CLI and curl.
- Browser
- Download file 455 MB
-
https://huggingface.co/deepvk/bert-base-uncased/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://deepvk/bert-base-uncased/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/deepvk/bert-base-uncased/resolve/main/pytorch_model.bin
455 MB
- Xet hash:
- 87135fc80ae07851274f26ef8a87a0b78e5eb3e5f6cb79c9f1fe143b23ff4ad2
- Size of remote file:
- 455 MB
- SHA256:
- 1cfccccd0618f070fec77debdfc1b9f46e99c4633007de4a647a758b775da77b
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