Sentence Similarity
sentence-transformers
PyTorch
English
qwen3
feature-extraction
formbench
patent-retrieval
chemistry
formulations
materials-science
text-embeddings-inference
Instructions to use Formbench-anon/qwen3-embed-formbench-mnrl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Formbench-anon/qwen3-embed-formbench-mnrl with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Formbench-anon/qwen3-embed-formbench-mnrl") 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:
- 8ce28cb499ddb0a369f70df095bcfdaf8f41e9a70ee7c13a713d0cda2a0f7e81
- Size of remote file:
- 4.77 GB
- SHA256:
- 8369e141d19074d1c3eca876eeb5c90ac5e612eb9277ccddd39f96d9686f1e9c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.