Yi-1.5-9B-Chat-GGUF / README.md
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---
base_model: 01-ai/Yi-1.5-9B-Chat
inference: false
license: other
license_link: LICENSE
license_name: yi-license
model_creator: 01-ai
model_name: Yi-1.5-9B-Chat
model_type: yi
pipeline_tag: text-generation
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;">
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# Yi-1.5-9B-Chat-GGUF
## Original Model
[01-ai/Yi-1.5-9B-Chat](https://huggingface.co/01-ai/Yi-1.5-9B-Chat)
## Run with LlamaEdge
<!-- - LlamaEdge version: [v0.10.0](https://github.com/LlamaEdge/LlamaEdge/releases/tag/0.10.0) and above -->
- LlamaEdge version: coming soon
- Prompt template
- Prompt type: `chatml`
- Prompt string
```text
<|im_start|>system
{system_message}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
```
- Reverse prompt: `<|im_end|>`
- Context size: `4096`
- Run as LlamaEdge service
```bash
wasmedge --dir .:. --nn-preload default:GGML:AUTO:Yi-1.5-9B-Chat-Q5_K_M.gguf \
llama-api-server.wasm \
--prompt-template chatml \
--reverse-prompt "<|im_end|>" \
--ctx-size 4096 \
--model-name Yi-1.5-9B-Chat
```
- Run as LlamaEdge command app
```bash
wasmedge --dir .:. --nn-preload default:GGML:AUTO:Yi-1.5-9B-Chat-Q5_K_M.gguf \
llama-chat.wasm \
--prompt-template chatml \
--reverse-prompt "<|im_end|>" \
--ctx-size 4096
```
## Quantized GGUF Models
| Name | Quant method | Bits | Size | Use case |
| ---- | ---- | ---- | ---- | ----- |
| [Yi-1.5-9B-Chat-Q2_K.gguf](https://huggingface.co/second-state/Yi-1.5-9B-Chat-GGUF/blob/main/Yi-1.5-9B-Chat-Q2_K.gguf) | Q2_K | 2 |3.35 GB| smallest, significant quality loss - not recommended for most purposes |
| [Yi-1.5-9B-Chat-Q3_K_L.gguf](https://huggingface.co/second-state/Yi-1.5-9B-Chat-GGUF/blob/main/Yi-1.5-9B-Chat-Q3_K_L.gguf) | Q3_K_L | 3 | 3.24 GB| small, substantial quality loss |
| [Yi-1.5-9B-Chat-Q3_K_M.gguf](https://huggingface.co/second-state/Yi-1.5-9B-Chat-GGUF/blob/main/Yi-1.5-9B-Chat-Q3_K_M.gguf) | Q3_K_M | 3 | 2.99 GB| very small, high quality loss |
| [Yi-1.5-9B-Chat-Q3_K_S.gguf](https://huggingface.co/second-state/Yi-1.5-9B-Chat-GGUF/blob/main/Yi-1.5-9B-Chat-Q3_K_S.gguf) | Q3_K_S | 3 | 2.71 GB| very small, high quality loss |
| [Yi-1.5-9B-Chat-Q4_0.gguf](https://huggingface.co/second-state/Yi-1.5-9B-Chat-GGUF/blob/main/Yi-1.5-9B-Chat-Q4_0.gguf) | Q4_0 | 4 | 3.48 GB| legacy; small, very high quality loss - prefer using Q3_K_M |
| [Yi-1.5-9B-Chat-Q4_K_M.gguf](https://huggingface.co/second-state/Yi-1.5-9B-Chat-GGUF/blob/main/Yi-1.5-9B-Chat-Q4_K_M.gguf) | Q4_K_M | 4 | 3.67 GB| medium, balanced quality - recommended |
| [Yi-1.5-9B-Chat-Q4_K_S.gguf](https://huggingface.co/second-state/Yi-1.5-9B-Chat-GGUF/blob/main/Yi-1.5-9B-Chat-Q4_K_S.gguf) | Q4_K_S | 4 | 3.50 GB| small, greater quality loss |
| [Yi-1.5-9B-Chat-Q5_0.gguf](https://huggingface.co/second-state/Yi-1.5-9B-Chat-GGUF/blob/main/Yi-1.5-9B-Chat-Q5_0.gguf) | Q5_0 | 5 | 4.20 GB| legacy; medium, balanced quality - prefer using Q4_K_M |
| [Yi-1.5-9B-Chat-Q5_K_M.gguf](https://huggingface.co/second-state/Yi-1.5-9B-Chat-GGUF/blob/main/Yi-1.5-9B-Chat-Q5_K_M.gguf) | Q5_K_M | 5 | 4.30 GB| large, very low quality loss - recommended |
| [Yi-1.5-9B-Chat-Q5_K_S.gguf](https://huggingface.co/second-state/Yi-1.5-9B-Chat-GGUF/blob/main/Yi-1.5-9B-Chat-Q5_K_S.gguf) | Q5_K_S | 5 | 4.20 GB| large, low quality loss - recommended |
| [Yi-1.5-9B-Chat-Q6_K.gguf](https://huggingface.co/second-state/Yi-1.5-9B-Chat-GGUF/blob/main/Yi-1.5-9B-Chat-Q6_K.gguf) | Q6_K | 6 | 4.97 GB| very large, extremely low quality loss |
| [Yi-1.5-9B-Chat-Q8_0.gguf](https://huggingface.co/second-state/Yi-1.5-9B-Chat-GGUF/blob/main/Yi-1.5-9B-Chat-Q8_0.gguf) | Q8_0 | 8 | 6.44 GB| very large, extremely low quality loss - not recommended |
| [Yi-1.5-9B-Chat-f16.gguf](https://huggingface.co/second-state/Yi-1.5-9B-Chat-GGUF/blob/main/Yi-1.5-9B-Chat-f16.gguf) | f16 | 16 | 17.7 GB| |
*Quantized with llama.cpp b2824*