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README.md

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 ---
+base_model: Alibaba-NLP/gte-Qwen2-7B-instruct
 license: apache-2.0
+model_creator: Alibaba-NLP
+model_name: gte-Qwen2-7B-instruct
+quantized_by: Second State Inc.
 ---
+
+<!-- header start -->
+<!-- 200823 -->
+<div style="width: auto; margin-left: auto; margin-right: auto">
+<img src="https://github.com/LlamaEdge/LlamaEdge/raw/dev/assets/logo.svg" style="width: 100%; min-width: 400px; display: block; margin: auto;">
+</div>
+<hr style="margin-top: 1.0em; margin-bottom: 1.0em;">
+<!-- header end -->
+
+# gte-Qwen2-7B-instruct-GGUF
+
+## Original Model
+
+[Alibaba-NLP/gte-Qwen2-7B-instruct](https://huggingface.co/Alibaba-NLP/gte-Qwen2-7B-instruct)
+
+## Run with LlamaEdge
+
+- LlamaEdge version: [v0.16.8](https://github.com/LlamaEdge/LlamaEdge/releases/tag/0.16.8)
+
+- Prompt template
+
+  - Prompt type: `embedding`
+
+- Context size: `128000`
+
+- Run as LlamaEdge service
+
+  ```bash
+  wasmedge --dir .:. --nn-preload default:GGML:AUTO:gte-Qwen2-7B-instruct-Q5_K_M.gguf \
+    llama-api-server.wasm \
+    --model-name gte-Qwen2-7B-instruct \
+    --prompt-template embedding \
+    --ctx-size 128000
+  ```
+
+## Quantized GGUF Models
+
+| Name | Quant method | Bits | Size | Use case |
+| ---- | ---- | ---- | ---- | ----- |
+| [gte-Qwen2-7B-instruct-Q2_K.gguf](https://huggingface.co/second-state/gte-Qwen2-7B-instruct-GGUF/blob/main/gte-Qwen2-7B-instruct-Q2_K.gguf)     | Q2_K   | 2 | 3.01 GB| smallest, significant quality loss - not recommended for most purposes |
+| [gte-Qwen2-7B-instruct-Q3_K_L.gguf](https://huggingface.co/second-state/gte-Qwen2-7B-instruct-GGUF/blob/main/gte-Qwen2-7B-instruct-Q3_K_L.gguf) | Q3_K_L | 3 | 4.09 GB| small, substantial quality loss |
+| [gte-Qwen2-7B-instruct-Q3_K_M.gguf](https://huggingface.co/second-state/gte-Qwen2-7B-instruct-GGUF/blob/main/gte-Qwen2-7B-instruct-Q3_K_M.gguf) | Q3_K_M | 3 | 3.81 GB| very small, high quality loss |
+| [gte-Qwen2-7B-instruct-Q3_K_S.gguf](https://huggingface.co/second-state/gte-Qwen2-7B-instruct-GGUF/blob/main/gte-Qwen2-7B-instruct-Q3_K_S.gguf) | Q3_K_S | 3 | 3.49 GB| very small, high quality loss |
+| [gte-Qwen2-7B-instruct-Q4_0.gguf](https://huggingface.co/second-state/gte-Qwen2-7B-instruct-GGUF/blob/main/gte-Qwen2-7B-instruct-Q4_0.gguf)     | Q4_0   | 4 | 4.43 GB| legacy; small, very high quality loss - prefer using Q3_K_M |
+| [gte-Qwen2-7B-instruct-Q4_K_M.gguf](https://huggingface.co/second-state/gte-Qwen2-7B-instruct-GGUF/blob/main/gte-Qwen2-7B-instruct-Q4_K_M.gguf) | Q4_K_M | 4 | 4.68 GB| medium, balanced quality - recommended |
+| [gte-Qwen2-7B-instruct-Q4_K_S.gguf](https://huggingface.co/second-state/gte-Qwen2-7B-instruct-GGUF/blob/main/gte-Qwen2-7B-instruct-Q4_K_S.gguf) | Q4_K_S | 4 | 4.46 GB| small, greater quality loss |
+| [gte-Qwen2-7B-instruct-Q5_0.gguf](https://huggingface.co/second-state/gte-Qwen2-7B-instruct-GGUF/blob/main/gte-Qwen2-7B-instruct-Q5_0.gguf)     | Q5_0   | 5 | 5.31 GB| legacy; medium, balanced quality - prefer using Q4_K_M |
+| [gte-Qwen2-7B-instruct-Q5_K_M.gguf](https://huggingface.co/second-state/gte-Qwen2-7B-instruct-GGUF/blob/main/gte-Qwen2-7B-instruct-Q5_K_M.gguf) | Q5_K_M | 5 | 5.44 GB| large, very low quality loss - recommended |
+| [gte-Qwen2-7B-instruct-Q5_K_S.gguf](https://huggingface.co/second-state/gte-Qwen2-7B-instruct-GGUF/blob/main/gte-Qwen2-7B-instruct-Q5_K_S.gguf) | Q5_K_S | 5 | 5.31 GB| large, low quality loss - recommended |
+| [gte-Qwen2-7B-instruct-Q6_K.gguf](https://huggingface.co/second-state/gte-Qwen2-7B-instruct-GGUF/blob/main/gte-Qwen2-7B-instruct-Q6_K.gguf)     | Q6_K   | 6 | 6.25 GB| very large, extremely low quality loss |
+| [gte-Qwen2-7B-instruct-Q8_0.gguf](https://huggingface.co/second-state/gte-Qwen2-7B-instruct-GGUF/blob/main/gte-Qwen2-7B-instruct-Q8_0.gguf)     | Q8_0   | 8 | 8.10 GB| very large, extremely low quality loss - not recommended |
+| [gte-Qwen2-7B-instruct-f16.gguf](https://huggingface.co/second-state/gte-Qwen2-7B-instruct-GGUF/blob/main/gte-Qwen2-7B-instruct-f16.gguf)       | f16    | 16 | 15.2 GB| |
+
+*Quantized with llama.cpp b4754*