Sentence Similarity
PEFT
Safetensors
sentence-transformers
lora
semantic-search
faiss
hnsw
mathlib4
lean4
Instructions to use Isaac74/qwen3-0.6b-lightweight-semantic-mathlib-search-adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Isaac74/qwen3-0.6b-lightweight-semantic-mathlib-search-adapter with PEFT:
Task type is invalid.
- sentence-transformers
How to use Isaac74/qwen3-0.6b-lightweight-semantic-mathlib-search-adapter with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Isaac74/qwen3-0.6b-lightweight-semantic-mathlib-search-adapter") 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:
- 8c9af92b004e19c3a76e0f5a713c8b07ba1d8918b8072c0e71e876b8f5127e8d
- Size of remote file:
- 2.56 GB
- SHA256:
- 75b0424fc67e9f9df5df2d5e253ce600a93c25f0953bd0ecf41476c4483c83d2
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