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Pringled merged 1 commit into from
Nov 14, 2025
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docs: Update default model for example #299

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6 changes: 3 additions & 3 deletions README.md
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Expand Up @@ -41,7 +41,7 @@



Model2Vec is a technique to turn any sentence transformer into a small, fast static embedding model. Model2Vec reduces model size by a factor up to 50 and makes models up to 500 times faster, with a small drop in performance. Our [best model](https://huggingface.co/minishlab/potion-base-8M) is the most performant static embedding model in the world. See our [results](results/README.md), read our [docs](https://minish.ai/packages/model2vec/introduction), or dive in to see how it works.
Model2Vec is a technique to turn any sentence transformer into a small, fast static embedding model. Model2Vec reduces model size by a factor up to 50 and makes models up to 500 times faster, with a small drop in performance. Our [best model](https://huggingface.co/minishlab/potion-base-32M) is the most performant static embedding model in the world. See our [results](results/README.md), read our [docs](https://minish.ai/packages/model2vec/introduction), or dive in to see how it works.

<div align="center">
<h3>
Expand All @@ -62,8 +62,8 @@ You can start using Model2Vec by loading one of our [flagship models from the Hu
```python
from model2vec import StaticModel

# Load a model from the HuggingFace hub (in this case the potion-base-8M model)
model = StaticModel.from_pretrained("minishlab/potion-base-8M")
# Load a model from the HuggingFace hub (in this case the potion-base-32M model)
model = StaticModel.from_pretrained("minishlab/potion-base-32M")

# Make embeddings
embeddings = model.encode(["It's dangerous to go alone!", "It's a secret to everybody."])
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