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---
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tags:
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- mteb
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- sentence-transformers
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- transformers
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- Qwen2
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- sentence-similarity
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license: apache-2.0
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base_model: Alibaba-NLP/gte-Qwen2-1.5B-instruct
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model_creator: intfloat
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quantized_by: Second State Inc.
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---
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<!-- header start -->
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<!-- 200823 -->
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<div style="width: auto; margin-left: auto; margin-right: auto">
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<img src="https://github.com/LlamaEdge/LlamaEdge/raw/dev/assets/logo.svg" style="width: 100%; min-width: 400px; display: block; margin: auto;">
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</div>
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<hr style="margin-top: 1.0em; margin-bottom: 1.0em;">
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<!-- header end -->
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# gte-Qwen2-1.5B-instruct-GGUF
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## Original Model
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[Alibaba-NLP/gte-Qwen2-1.5B-instruct](https://huggingface.co/Alibaba-NLP/gte-Qwen2-1.5B-instruct)
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## Run with LlamaEdge
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- LlamaEdge version: [v0.12.2](https://github.com/LlamaEdge/LlamaEdge/releases/tag/0.12.2) and above
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- Prompt template
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- Prompt type: `embedding`
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- Context size: `32000`
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- Run as LlamaEdge service
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```bash
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wasmedge --dir .:. --nn-preload default:GGML:AUTO:gte-Qwen2-1.5B-instruct-Q5_K_M.gguf \
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llama-api-server.wasm \
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--prompt-template embedding \
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--ctx-size 32000 \
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--model-name gte-Qwen2-1.5B-instruct
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```
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## Quantized GGUF Models
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| Name | Quant method | Bits | Size | Use case |
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| ---- | ---- | ---- | ---- | ----- |
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| [gte-Qwen2-1.5B-instruct-Q2_K.gguf](https://huggingface.co/second-state/gte-Qwen2-1.5B-instruct-GGUF/blob/main/gte-Qwen2-1.5B-instruct-Q2_K.gguf) | Q2_K | 2 | 752 MB| smallest, significant quality loss - not recommended for most purposes |
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| [gte-Qwen2-1.5B-instruct-Q3_K_L.gguf](https://huggingface.co/second-state/gte-Qwen2-1.5B-instruct-GGUF/blob/main/gte-Qwen2-1.5B-instruct-Q3_K_L.gguf) | Q3_K_L | 3 | 980 MB| small, substantial quality loss |
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| [gte-Qwen2-1.5B-instruct-Q3_K_M.gguf](https://huggingface.co/second-state/gte-Qwen2-1.5B-instruct-GGUF/blob/main/gte-Qwen2-1.5B-instruct-Q3_K_M.gguf) | Q3_K_M | 3 | 924 MB| very small, high quality loss |
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| [gte-Qwen2-1.5B-instruct-Q3_K_S.gguf](https://huggingface.co/second-state/gte-Qwen2-1.5B-instruct-GGUF/blob/main/gte-Qwen2-1.5B-instruct-Q3_K_S.gguf) | Q3_K_S | 3 | 861 MB| very small, high quality loss |
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| [gte-Qwen2-1.5B-instruct-Q4_0.gguf](https://huggingface.co/second-state/gte-Qwen2-1.5B-instruct-GGUF/blob/main/gte-Qwen2-1.5B-instruct-Q4_0.gguf) | Q4_0 | 4 | 1.07 GB| legacy; small, very high quality loss - prefer using Q3_K_M |
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| [gte-Qwen2-1.5B-instruct-Q4_K_M.gguf](https://huggingface.co/second-state/gte-Qwen2-1.5B-instruct-GGUF/blob/main/gte-Qwen2-1.5B-instruct-Q4_K_M.gguf) | Q4_K_M | 4 | 1.12 GB| medium, balanced quality - recommended |
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| [gte-Qwen2-1.5B-instruct-Q4_K_S.gguf](https://huggingface.co/second-state/gte-Qwen2-1.5B-instruct-GGUF/blob/main/gte-Qwen2-1.5B-instruct-Q4_K_S.gguf) | Q4_K_S | 4 | 1.07 GB| small, greater quality loss |
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| [gte-Qwen2-1.5B-instruct-Q5_0.gguf](https://huggingface.co/second-state/gte-Qwen2-1.5B-instruct-GGUF/blob/main/gte-Qwen2-1.5B-instruct-Q5_0.gguf) | Q5_0 | 5 | 1.26 GB| legacy; medium, balanced quality - prefer using Q4_K_M |
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| [gte-Qwen2-1.5B-instruct-Q5_K_M.gguf](https://huggingface.co/second-state/gte-Qwen2-1.5B-instruct-GGUF/blob/main/gte-Qwen2-1.5B-instruct-Q5_K_M.gguf) | Q5_K_M | 5 | 1.28 GB| large, very low quality loss - recommended |
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| [gte-Qwen2-1.5B-instruct-Q5_K_S.gguf](https://huggingface.co/second-state/gte-Qwen2-1.5B-instruct-GGUF/blob/main/gte-Qwen2-1.5B-instruct-Q5_K_S.gguf) | Q5_K_S | 5 | 1.26 GB| large, low quality loss - recommended |
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| [gte-Qwen2-1.5B-instruct-Q6_K.gguf](https://huggingface.co/second-state/gte-Qwen2-1.5B-instruct-GGUF/blob/main/gte-Qwen2-1.5B-instruct-Q6_K.gguf) | Q6_K | 6 | 1.46 GB| very large, extremely low quality loss |
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| [gte-Qwen2-1.5B-instruct-Q8_0.gguf](https://huggingface.co/second-state/gte-Qwen2-1.5B-instruct-GGUF/blob/main/gte-Qwen2-1.5B-instruct-Q8_0.gguf) | Q8_0 | 8 | 1.89 GB| very large, extremely low quality loss - not recommended |
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| [gte-Qwen2-1.5B-instruct-f16.gguf](https://huggingface.co/second-state/gte-Qwen2-1.5B-instruct-GGUF/blob/main/gte-Qwen2-1.5B-instruct-f16.gguf) | f16 | 8 | 3.56 GB| very large, extremely low quality loss - not recommended |
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*Quantized with llama.cpp b3259* |
