Sentence Similarity
sentence-transformers
PyTorch
TensorFlow
Rust
ONNX
Safetensors
OpenVINO
Transformers
English
bert
feature-extraction
text-embeddings-inference
Instructions to use Karmukilan/all-MiniLM-L6-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Karmukilan/all-MiniLM-L6-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Karmukilan/all-MiniLM-L6-v2") 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 Karmukilan/all-MiniLM-L6-v2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Karmukilan/all-MiniLM-L6-v2") model = AutoModel.from_pretrained("Karmukilan/all-MiniLM-L6-v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0496be853af12b18b8ec269f1a7d2bb5312473420888e236ad2139e46c942ad8
- Size of remote file:
- 90.3 MB
- SHA256:
- 1de3905029190b398c7d300b530e320cf4b5e7d3dfb9af1429ebd73fd9a16faf
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