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---
base_model: microsoft/Phi-3.5-mini-instruct
license: mit
license_link: https://huggingface.co/microsoft/Phi-3.5-mini-instruct/resolve/main/LICENSE
language:
- multilingual
pipeline_tag: text-generation
library_name: transformers
model_creator: Microsoft
model_name: Phi-3.5-mini-instruct
quantized_by: Second State Inc.
tags:
- nlp
- code
---
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# Phi-3.5-mini-instruct-GGUF
## Original Model
[microsoft/Phi-3.5-mini-instruct](https://huggingface.co/microsoft/Phi-3.5-mini-instruct)
## Run with LlamaEdge
- LlamaEdge version: [v0.14.0](https://github.com/LlamaEdge/LlamaEdge/releases/tag/0.14.0) and above
- Prompt template
- Prompt type: `phi-3-chat`
- Prompt string
```text
<|system|>
{system_message}<|end|>
<|user|>
{user_message_1}<|end|>
<|assistant|>
{assistant_message_1}<|end|>
<|user|>
{user_message_2}<|end|>
<|assistant|>
```
- Context size: `128000`
- Run as LlamaEdge service
```bash
wasmedge --dir .:. --nn-preload default:GGML:AUTO:Phi-3.5-mini-instruct-Q5_K_M.gguf \
llama-api-server.wasm \
--prompt-template phi-3-chat \
--ctx-size 128000 \
--model-name phi-3-mini
```
- Run as LlamaEdge command app
```bash
wasmedge --dir .:. --nn-preload default:GGML:AUTO:Phi-3.5-mini-instruct-Q5_K_M.gguf \
llama-chat.wasm \
--prompt-template phi-3-chat \
--ctx-size 128000
```
## Quantized GGUF Models
| Name | Quant method | Bits | Size | Use case |
| ---- | ---- | ---- | ---- | ----- |
| [Phi-3.5-mini-instruct-Q2_K.gguf](https://huggingface.co/second-state/Phi-3.5-mini-instruct-GGUF/blob/main/Phi-3.5-mini-instruct-Q2_K.gguf) | Q2_K | 2 | 1.42 GB| smallest, significant quality loss - not recommended for most purposes |
| [Phi-3.5-mini-instruct-Q3_K_L.gguf](https://huggingface.co/second-state/Phi-3.5-mini-instruct-GGUF/blob/main/Phi-3.5-mini-instruct-Q3_K_L.gguf) | Q3_K_L | 3 | 2.09 GB| small, substantial quality loss |
| [Phi-3.5-mini-instruct-Q3_K_M.gguf](https://huggingface.co/second-state/Phi-3.5-mini-instruct-GGUF/blob/main/Phi-3.5-mini-instruct-Q3_K_M.gguf) | Q3_K_M | 3 | 1.96 GB| very small, high quality loss |
| [Phi-3.5-mini-instruct-Q3_K_S.gguf](https://huggingface.co/second-state/Phi-3.5-mini-instruct-GGUF/blob/main/Phi-3.5-mini-instruct-Q3_K_S.gguf) | Q3_K_S | 3 | 1.68 GB| very small, high quality loss |
| [Phi-3.5-mini-instruct-Q4_0.gguf](https://huggingface.co/second-state/Phi-3.5-mini-instruct-GGUF/blob/main/Phi-3.5-mini-instruct-Q4_0.gguf) | Q4_0 | 4 | 2.18 GB| legacy; small, very high quality loss - prefer using Q3_K_M |
| [Phi-3.5-mini-instruct-Q4_K_M.gguf](https://huggingface.co/second-state/Phi-3.5-mini-instruct-GGUF/blob/main/Phi-3.5-mini-instruct-Q4_K_M.gguf) | Q4_K_M | 4 | 2.39 GB| medium, balanced quality - recommended |
| [Phi-3.5-mini-instruct-Q4_K_S.gguf](https://huggingface.co/second-state/Phi-3.5-mini-instruct-GGUF/blob/main/Phi-3.5-mini-instruct-Q4_K_S.gguf) | Q4_K_S | 4 | 2.19 GB| small, greater quality loss |
| [Phi-3.5-mini-instruct-Q5_0.gguf](https://huggingface.co/second-state/Phi-3.5-mini-instruct-GGUF/blob/main/Phi-3.5-mini-instruct-Q5_0.gguf) | Q5_0 | 5 | 2.64 GB| legacy; medium, balanced quality - prefer using Q4_K_M |
| [Phi-3.5-mini-instruct-Q5_K_M.gguf](https://huggingface.co/second-state/Phi-3.5-mini-instruct-GGUF/blob/main/Phi-3.5-mini-instruct-Q5_K_M.gguf) | Q5_K_M | 5 | 2.82 GB| large, very low quality loss - recommended |
| [Phi-3.5-mini-instruct-Q5_K_S.gguf](https://huggingface.co/second-state/Phi-3.5-mini-instruct-GGUF/blob/main/Phi-3.5-mini-instruct-Q5_K_S.gguf) | Q5_K_S | 5 | 2.64 GB| large, low quality loss - recommended |
| [Phi-3.5-mini-instruct-Q6_K.gguf](https://huggingface.co/second-state/Phi-3.5-mini-instruct-GGUF/blob/main/Phi-3.5-mini-instruct-Q6_K.gguf) | Q6_K | 6 | 3.14 GB| very large, extremely low quality loss |
| [Phi-3.5-mini-instruct-Q8_0.gguf](https://huggingface.co/second-state/Phi-3.5-mini-instruct-GGUF/blob/main/Phi-3.5-mini-instruct-Q8_0.gguf) | Q8_0 | 8 | 4.06 GB| very large, extremely low quality loss - not recommended |
| [Phi-3.5-mini-instruct-f16.gguf](https://huggingface.co/second-state/Phi-3.5-mini-instruct-GGUF/blob/main/Phi-3.5-mini-instruct-f16.gguf) | f16 | 16 | 7.64 GB| |
*Quantized with llama.cpp b3499.*