Instructions to use r2d2/stsb-bertweet-base-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use r2d2/stsb-bertweet-base-v0 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("r2d2/stsb-bertweet-base-v0") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use r2d2/stsb-bertweet-base-v0 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("r2d2/stsb-bertweet-base-v0") model = AutoModel.from_pretrained("r2d2/stsb-bertweet-base-v0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f704aed13f5a345f495445dfde0423d7df1e8616bb90de48e1b081136e58e85d
- Size of remote file:
- 540 MB
- SHA256:
- 6dfb52f01ccd262884bbb7b3da18dffaf1973b9e35f4192c2c28919d0ca10f73
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