Sentence Similarity
sentence-transformers
PyTorch
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use kamalkraj/BioSimCSE-BioLinkBERT-BASE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use kamalkraj/BioSimCSE-BioLinkBERT-BASE with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("kamalkraj/BioSimCSE-BioLinkBERT-BASE") sentences = [ "The up-regulation of miR-146a was also detected in cervical cancer tissues.", "The expression of miR-146a has been found to be up-regulated in cervical cancer.", "Only concomitant ablation of ERK1 and ERK2 impairs tumor growth." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Transformers
How to use kamalkraj/BioSimCSE-BioLinkBERT-BASE with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("kamalkraj/BioSimCSE-BioLinkBERT-BASE") model = AutoModel.from_pretrained("kamalkraj/BioSimCSE-BioLinkBERT-BASE", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model
Verified signatureThis 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.7567548
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