Model2Vec
ONNX
Safetensors
sentence-transformers
embeddings
static-embeddings
mteb
Eval Results (legacy)
Instructions to use SethBurkart/potion-base-8m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Model2Vec
How to use SethBurkart/potion-base-8m with Model2Vec:
from model2vec import StaticModel model = StaticModel.from_pretrained("SethBurkart/potion-base-8m") - sentence-transformers
How to use SethBurkart/potion-base-8m with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("SethBurkart/potion-base-8m") 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] - Notebooks
- Google Colab
- Kaggle
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