Instructions to use tdro-llm/s2-tdro-Mistral-7B-v0.1-top70 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use tdro-llm/s2-tdro-Mistral-7B-v0.1-top70 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("tdro-llm/s2-tdro-Mistral-7B-v0.1-top70") 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:
- 70fd90f47b98ae4122cb47b23b9093f202a552b539c0a98f6c68b2ba4142377d
- Size of remote file:
- 5.5 kB
- SHA256:
- 8f024bd7764e69a71addef975a839d9ffe513ffb005eac04930d2ba8e558184e
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