---
base_model: intfloat/e5-mistral-7b-instruct
license: mit
model_creator: intfloat
quantized_by: Second State Inc.
language: en
---

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# E5-Mistral-7B-Instruct-Embedding-GGUF

## Original Model

[intfloat/e5-mistral-7b-instruct](https://huggingface.co/intfloat/e5-mistral-7b-instruct)

## Run with LlamaEdge

- LlamaEdge version: [v0.8.2](https://github.com/LlamaEdge/LlamaEdge/releases/tag/0.8.2) and above

- Prompt template

  - Prompt type: `embedding`

- Context size: `4096`

- Run as LlamaEdge service

  ```bash
  wasmedge --dir .:. --nn-preload default:GGML:AUTO:e5-mistral-7b-instruct-Q5_K_M.gguf \
    llama-api-server.wasm \
    --prompt-template embedding \
    --ctx-size 4096 \
    --model-name e5-mistral-7b-instruct
  ```

## Quantized GGUF Models

| Name | Quant method | Bits | Size | Use case |
| ---- | ---- | ---- | ---- | ----- |
| [e5-mistral-7b-instruct-Q2_K.gguf](https://huggingface.co/second-state/E5-Mistral-7B-Instruct-Embedding-GGUF/blob/main/e5-mistral-7b-instruct-Q2_K.gguf)     | Q2_K   | 2 | 2.72 GB| smallest, significant quality loss - not recommended for most purposes |
| [e5-mistral-7b-instruct-Q3_K_L.gguf](https://huggingface.co/second-state/E5-Mistral-7B-Instruct-Embedding-GGUF/blob/main/e5-mistral-7b-instruct-Q3_K_L.gguf) | Q3_K_L | 3 | 3.82 GB| small, substantial quality loss |
| [e5-mistral-7b-instruct-Q3_K_M.gguf](https://huggingface.co/second-state/E5-Mistral-7B-Instruct-Embedding-GGUF/blob/main/e5-mistral-7b-instruct-Q3_K_M.gguf) | Q3_K_M | 3 | 3.52 GB| very small, high quality loss |
| [e5-mistral-7b-instruct-Q3_K_S.gguf](https://huggingface.co/second-state/E5-Mistral-7B-Instruct-Embedding-GGUF/blob/main/e5-mistral-7b-instruct-Q3_K_S.gguf) | Q3_K_S | 3 | 3.16 GB| very small, high quality loss |
| [e5-mistral-7b-instruct-Q4_0.gguf](https://huggingface.co/second-state/E5-Mistral-7B-Instruct-Embedding-GGUF/blob/main/e5-mistral-7b-instruct-Q4_0.gguf)     | Q4_0   | 4 | 4.11 GB| legacy; small, very high quality loss - prefer using Q3_K_M |
| [e5-mistral-7b-instruct-Q4_K_M.gguf](https://huggingface.co/second-state/E5-Mistral-7B-Instruct-Embedding-GGUF/blob/main/e5-mistral-7b-instruct-Q4_K_M.gguf) | Q4_K_M | 4 | 4.37 GB| medium, balanced quality - recommended |
| [e5-mistral-7b-instruct-Q4_K_S.gguf](https://huggingface.co/second-state/E5-Mistral-7B-Instruct-Embedding-GGUF/blob/main/e5-mistral-7b-instruct-Q4_K_S.gguf) | Q4_K_S | 4 | 4.14 GB| small, greater quality loss |
| [e5-mistral-7b-instruct-Q5_0.gguf](https://huggingface.co/second-state/E5-Mistral-7B-Instruct-Embedding-GGUF/blob/main/e5-mistral-7b-instruct-Q5_0.gguf)     | Q5_0   | 5 | 5.00 GB| legacy; medium, balanced quality - prefer using Q4_K_M |
| [e5-mistral-7b-instruct-Q5_K_M.gguf](https://huggingface.co/second-state/E5-Mistral-7B-Instruct-Embedding-GGUF/blob/main/e5-mistral-7b-instruct-Q5_K_M.gguf) | Q5_K_M | 5 | 5.13 GB| large, very low quality loss - recommended |
| [e5-mistral-7b-instruct-Q5_K_S.gguf](https://huggingface.co/second-state/E5-Mistral-7B-Instruct-Embedding-GGUF/blob/main/e5-mistral-7b-instruct-Q5_K_S.gguf) | Q5_K_S | 5 | 5.00 GB| large, low quality loss - recommended |
| [e5-mistral-7b-instruct-Q6_K.gguf](https://huggingface.co/second-state/E5-Mistral-7B-Instruct-Embedding-GGUF/blob/main/e5-mistral-7b-instruct-Q6_K.gguf)     | Q6_K   | 6 | 5.94 GB| very large, extremely low quality loss |
| [e5-mistral-7b-instruct-Q8_0.gguf](https://huggingface.co/second-state/E5-Mistral-7B-Instruct-Embedding-GGUF/blob/main/e5-mistral-7b-instruct-Q8_0.gguf)     | Q8_0   | 8 |  7.7 GB| very large, extremely low quality loss - not recommended |
| [e5-mistral-7b-instruct-f16.gguf](https://huggingface.co/second-state/E5-Mistral-7B-Instruct-Embedding-GGUF/blob/main/e5-mistral-7b-instruct-f16.gguf)       | f16    | 8 | 14.5 GB| very large, extremely low quality loss - not recommended |

*Quantized with llama.cpp b2334*