Feature Extraction
Transformers
PyTorch
Safetensors
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roberta
text-embeddings-inference
Instructions to use deepvk/roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepvk/roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="deepvk/roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("deepvk/roberta-base") model = AutoModel.from_pretrained("deepvk/roberta-base") - Notebooks
- Google Colab
- Kaggle
Commit ·
3aae27a
1
Parent(s): 7f3232e
Adding `safetensors` variant of this model
Browse filesThis is an automated PR created with https://huggingface.co/spaces/safetensors/convert
This new file is equivalent to `pytorch_model.bin` but safe in the sense that
no arbitrary code can be put into it.
These files also happen to load much faster than their pytorch counterpart:
https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb
The widgets on your model page will run using this model even if this is not merged
making sure the file actually works.
If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions
Feel free to ignore this PR.
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:14a76e9bd8e0fc9dbfaa2eac0ae32c9bf4954112cf53a030c5a2ce9805721688
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size 498609104
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