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glove-2024-dolma-quantized
NeuML/glove-2024-dolma-quantized
glove-2024-dolma-quantized is a sentence similarity model from NeuML. Use it when you need a score for how close two texts are. It is set up for staticvectors. The card lists the license as pddl.
This model is an export of the new GloVe 2024 Dolma Vectors (300d) for staticvectors. staticvectors enables running inference in Python with NumPy. This helps it maintain solid runtime performance.
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Model card
From the Hugging Face model README
GloVe 2024 Dolma StaticVectors model
This model is an export of the new GloVe 2024 Dolma Vectors (300d) for staticvectors. staticvectors enables running inference in Python with NumPy. This helps it maintain solid runtime performance.
This model is a quantized version of the base model. It's using 10x256 Product Quantization.
Usage with StaticVectors
from staticvectors import StaticVectors
model = StaticVectors("neuml/glove-2024-dolma-quantized")
model.embeddings(["word"])
- Task
- Sentence Similarity
- Library
- staticvectors
- Type
- staticvectors
- License
- pddl
- Languages
- en
- Created
- Jul 29, 2025
- Updated
- Jul 29, 2025