Instructions to use tdro-llm/s2-tdro-Qwen1.5-1.8B-curr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use tdro-llm/s2-tdro-Qwen1.5-1.8B-curr with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("tdro-llm/s2-tdro-Qwen1.5-1.8B-curr") 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] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a14291f9b93a984f4ad4ef01bd760bedc60026554fe25b620d1df6c16abb81ef
- Size of remote file:
- 15 MB
- SHA256:
- 8a9ca37ed71c6360186972c03065299497654dbf07f5d17198336b84eb298f18
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