Feature Extraction
sentence-transformers
PyTorch
Transformers
bert
sentence-similarity
text-embeddings-inference
Instructions to use Craig/paraphrase-MiniLM-L6-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Craig/paraphrase-MiniLM-L6-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Craig/paraphrase-MiniLM-L6-v2") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Transformers
How to use Craig/paraphrase-MiniLM-L6-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Craig/paraphrase-MiniLM-L6-v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Craig/paraphrase-MiniLM-L6-v2") model = AutoModel.from_pretrained("Craig/paraphrase-MiniLM-L6-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Craig/paraphrase-MiniLM-L6-v2: direct link, hf CLI and curl.
- Browser
- Download file 90.9 MB
-
https://huggingface.co/Craig/paraphrase-MiniLM-L6-v2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Craig/paraphrase-MiniLM-L6-v2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Craig/paraphrase-MiniLM-L6-v2/resolve/main/pytorch_model.bin
90.9 MB
- Xet hash:
- a8ff1a37310d6a5bda4a81e2c8653653d98d65fc01176dcba6bdbc0ebf2b3fe8
- Size of remote file:
- 90.9 MB
- SHA256:
- 5d716de760acbdc09e79a11e718c5606e0812b6aeb76c6664cba876d174e3ecd
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