---
tags:
- mteb
- sentence-transformers
- transformers
- Qwen2
- sentence-similarity
license: apache-2.0
base_model: Alibaba-NLP/gte-Qwen2-1.5B-instruct
model_creator: intfloat
quantized_by: Second State Inc.
---

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# gte-Qwen2-1.5B-instruct-GGUF

## Original Model

[Alibaba-NLP/gte-Qwen2-1.5B-instruct](https://huggingface.co./Alibaba-NLP/gte-Qwen2-1.5B-instruct)

## Run with LlamaEdge

- LlamaEdge version: [v0.12.2](https://github.com/LlamaEdge/LlamaEdge/releases/tag/0.12.2) and above

- Prompt template

  - Prompt type: `embedding`

- Context size: `32000`

- Run as LlamaEdge service

  ```bash
  wasmedge --dir .:. --nn-preload default:GGML:AUTO:gte-Qwen2-1.5B-instruct-Q5_K_M.gguf \
    llama-api-server.wasm \
    --prompt-template embedding \
    --ctx-size 32000 \
    --model-name gte-Qwen2-1.5B-instruct
  ```

## Quantized GGUF Models

| Name | Quant method | Bits | Size | Use case |
| ---- | ---- | ---- | ---- | ----- |
| [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 |
| [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 |
| [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 |
| [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 |
| [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 |
| [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 |
| [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 |
| [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 |
| [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 |
| [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 |
| [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 |
| [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 |
| [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 |

*Quantized with llama.cpp b3259*