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--- |
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license: llama3.2 |
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language: |
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- vi |
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base_model: |
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- meta-llama/Llama-3.2-1B-Instruct |
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pipeline_tag: sentence-similarity |
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library_name: transformers |
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--- |
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# misa-ai/Llama-3.2-1B-Instruct-Embedding-Base |
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This is a Embedding model for Document Retrieval: It maps sentences & paragraphs to a 2048 dimensional dense vector space and can be used for tasks like clustering or semantic search. |
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We train the model on a merged training dataset that consists of multiple domains, about 900k triplets in Vietnamese: |
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We use [Llama-3.2-1B-Instruct](https://github.com/meta-llama/Llama-3.2-1B-Instruct) as the pre-trained backbone. |
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This model directed to Document Retrieval. |
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Details: |
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- Max support context size: 4096 tokens |
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- Pooling last token (should use `padding_side = "left"`) |
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- Language: Vietnamese |
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- Prompts: |
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- Query: "Cho một câu truy vấn tìm kiếm thông tin, hãy truy xuất các tài liệu có liên quan trả lời cho truy vấn đó." |
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- Document: "" |
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### Please cite our manuscript if this dataset is used for your work |
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- Organization: MISA JSC |
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- Author: [Sy-The Ho](https://huggingface.co/thehosy) |
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