Sentence Similarity
sentence-transformers
PyTorch
Safetensors
Transformers
Polish
roberta
feature-extraction
text-embeddings-inference
Instructions to use radlab/polish-bi-encoder-mean with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use radlab/polish-bi-encoder-mean with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("radlab/polish-bi-encoder-mean") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Transformers
How to use radlab/polish-bi-encoder-mean with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("radlab/polish-bi-encoder-mean") model = AutoModel.from_pretrained("radlab/polish-bi-encoder-mean", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 135 Bytes
36cedcb | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:3250e4059abf3d6ad2d12dc0b78ab31213aa88b891be7df68472c466bf9d873b
size 1739977449
|