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Parent(s):
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Corrected Quick Start Instructions and Author Links
Browse files
README.md
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# lodestone-base-4096-v1
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[Hum-Works/lodestone-base-4096-v1](https://huggingface.co/Hum-Works/lodestone-base-4096-v1). [Griffin McCauley](https://
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This new [sentence-transformers](https://www.SBERT.net) model from [Hum](https://www.hum.works/) maps long sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
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```python
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from sentence_transformers import SentenceTransformer
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model = SentenceTransformer('lodestone-base-4096-v1', trust_remote_code=True, revision='v1.0.0')
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sentences = ["This is an example sentence", "Each sentence is converted"]
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embeddings = model.encode(sentences)
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print(embeddings)
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# lodestone-base-4096-v1
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[Hum-Works/lodestone-base-4096-v1](https://huggingface.co/Hum-Works/lodestone-base-4096-v1). [Griffin McCauley](https://huggingface.co/gmccaul1), [Will Fortin](https://huggingface.co/willathum), [Dylan DiGioia](https://huggingface.co/dylanAtHum) 2023
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This new [sentence-transformers](https://www.SBERT.net) model from [Hum](https://www.hum.works/) maps long sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
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```python
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from sentence_transformers import SentenceTransformer
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model = SentenceTransformer('Hum-Works/lodestone-base-4096-v1', trust_remote_code=True, revision='v1.0.0')
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sentences = ["This is an example sentence", "Each sentence is converted"]
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embeddings = model.encode(sentences)
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print(embeddings)
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