Sentence Similarity
Safetensors
sentence-transformers
PyLate
lfm2
liquid
lfm2.5
edge
ColBERT
feature-extraction
custom_code
Instructions to use LiquidAI/LFM2.5-ColBERT-350M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use LiquidAI/LFM2.5-ColBERT-350M with sentence-transformers:
from pylate import models queries = [ "Which planet is known as the Red Planet?", "What is the largest planet in our solar system?", ] documents = [ ["Mars is the Red Planet.", "Venus is Earth's twin."], ["Jupiter is the largest planet.", "Saturn has rings."], ] model = models.ColBERT(model_name_or_path="LiquidAI/LFM2.5-ColBERT-350M") queries_emb = model.encode(queries, is_query=True) docs_emb = model.encode(documents, is_query=False) - Notebooks
- Google Colab
- Kaggle
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| LFM2.5-ColBERT-350M | Query embedding + MaxSim | yes | 8.2 ms | 15.2 ms |
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| LFM2.5-ColBERT-350M | Query embedding + Doc embedding + MaxSim | no | 34.3 ms | 36.3 ms |
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Both models [LiquidAI/LFM2.5-ColBERT-350M-GGUF](https://huggingface.co/LiquidAI/LFM2.5-ColBERT-350M-GGUF/) and [LiquidAI/LFM2.5-Embedding-350M-GGUF](https://huggingface.co/LiquidAI/LFM2.5-Embedding-350M-GGUF/) are available
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## 📬 Contact
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| LFM2.5-ColBERT-350M | Query embedding + MaxSim | yes | 8.2 ms | 15.2 ms |
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| LFM2.5-ColBERT-350M | Query embedding + Doc embedding + MaxSim | no | 34.3 ms | 36.3 ms |
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Both models [LiquidAI/LFM2.5-ColBERT-350M-GGUF](https://huggingface.co/LiquidAI/LFM2.5-ColBERT-350M-GGUF/) and [LiquidAI/LFM2.5-Embedding-350M-GGUF](https://huggingface.co/LiquidAI/LFM2.5-Embedding-350M-GGUF/) are available on Hugging Face under different quantization schemas for llama.cpp.
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## 📬 Contact
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