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Hi.
First of all, thank you for making such a model available to us.
I am trying to get vector embeddings of abstracts of some of the articles in PubMed. But somehow I couldn't get the sentence embe…
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Great paper towards expanding translations for accessibility! https://aclanthology.org/2024.acl-short.40/
Looking forward for the code to be uploaded!
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Our current approach embeds datasets using Sentence Transformers that give us one embedding per "chunk" of text (so if we pass in 500 tokens of text or 100 tokens of text we always get 1 embedding). S…
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## Overview
This is a global tracking issue to bring generic sentence embedding models to MLCEngine.
## Action Items
- [ ] Add support for mistral based sentence embedding
## L…
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### What is the bug?
I am using text_chunking and text_embedding processor to ingest documents into an index. The [text_chunking search example](https://opensearch.org/docs/latest/search-plugins/text…
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I am trying to use embedding API with this code:
`List embeddings = embeddingModel.embed(List.of("Hello world", "How are you?"));`
Getting:
`ai.onnxruntime.OrtException: Supplied array is ragge…
JirHr updated
3 weeks ago
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hi, as the author say, the sentence embedding should be the output of the final step, it's conflict with the your code——reduce_sum
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I would like to compute sentence embeddings. Are any of your pretrained models suitable for that? I want to use the Sentence Transformer (https://www.sbert.net/examples/applications/computing-embeddin…
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### Describe the bug
rag_app.py line: 125:
elif "text2vec" in app.state.RAG_EMBEDDING_MODEL:
app.state.sentence_transformer_ef = embedding_functions.Text2VecEmbeddingFunction(
model_…
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I am using infersent to embed sentences. Also at some point i want to decode embedding back to sentence. i tried infersent.decode(sentences) and got following error.
AttributeError: 'InferSent' obj…