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---
base_model: deepseek-ai/DeepSeek-Coder-V2-Instruct
inference: false
library_name: gguf
license: other
license_link: LICENSE
license_name: deepseek-license
pipeline_tag: text-generation
quantized_by: legraphista
tags:
- quantized
- GGUF
- quantization
- imat
- imatrix
- static
- 6bit
- 5bit
- 4bit
- 3bit
- 2bit
- 1bit
---
# DeepSeek-Coder-V2-Instruct-IMat-GGUF
_Llama.cpp imatrix quantization of deepseek-ai/DeepSeek-Coder-V2-Instruct_
Original Model: [deepseek-ai/DeepSeek-Coder-V2-Instruct](https://huggingface.co./deepseek-ai/DeepSeek-Coder-V2-Instruct)
Original dtype: `BF16` (`bfloat16`)
Quantized by: llama.cpp [b3166](https://github.com/ggerganov/llama.cpp/releases/tag/b3166)
IMatrix dataset: [here](https://gist.githubusercontent.com/bartowski1182/eb213dccb3571f863da82e99418f81e8/raw/b2869d80f5c16fd7082594248e80144677736635/calibration_datav3.txt)
- [Files](#files)
- [IMatrix](#imatrix)
- [Common Quants](#common-quants)
- [All Quants](#all-quants)
- [Downloading using huggingface-cli](#downloading-using-huggingface-cli)
- [Inference](#inference)
- [Simple chat template](#simple-chat-template)
- [Chat template with system prompt](#chat-template-with-system-prompt)
- [Llama.cpp](#llama-cpp)
- [FAQ](#faq)
- [Why is the IMatrix not applied everywhere?](#why-is-the-imatrix-not-applied-everywhere)
- [How do I merge a split GGUF?](#how-do-i-merge-a-split-gguf)
---
## Files
### IMatrix
Status: ✅ Available
Link: [here](https://huggingface.co./legraphista/DeepSeek-Coder-V2-Instruct-IMat-GGUF/blob/main/imatrix.dat)
### Common Quants
| Filename | Quant type | File Size | Status | Uses IMatrix | Is Split |
| -------- | ---------- | --------- | ------ | ------------ | -------- |
| DeepSeek-Coder-V2-Instruct.Q6_K | Q6_K | - | ⏳ Processing | ⚪ Static | -
| [DeepSeek-Coder-V2-Instruct.Q4_K/*](https://huggingface.co./legraphista/DeepSeek-Coder-V2-Instruct-IMat-GGUF/tree/main/DeepSeek-Coder-V2-Instruct.Q4_K) | Q4_K | 142.45GB | ✅ Available | 🟢 IMatrix | ✂ Yes
| DeepSeek-Coder-V2-Instruct.Q3_K | Q3_K | - | ⏳ Processing | 🟢 IMatrix | -
| DeepSeek-Coder-V2-Instruct.Q2_K | Q2_K | - | ⏳ Processing | 🟢 IMatrix | -
### All Quants
| Filename | Quant type | File Size | Status | Uses IMatrix | Is Split |
| -------- | ---------- | --------- | ------ | ------------ | -------- |
| DeepSeek-Coder-V2-Instruct.Q6_K | Q6_K | - | ⏳ Processing | ⚪ Static | -
| DeepSeek-Coder-V2-Instruct.Q5_K | Q5_K | - | ⏳ Processing | ⚪ Static | -
| DeepSeek-Coder-V2-Instruct.Q5_K_S | Q5_K_S | - | ⏳ Processing | ⚪ Static | -
| [DeepSeek-Coder-V2-Instruct.Q4_K/*](https://huggingface.co./legraphista/DeepSeek-Coder-V2-Instruct-IMat-GGUF/tree/main/DeepSeek-Coder-V2-Instruct.Q4_K) | Q4_K | 142.45GB | ✅ Available | 🟢 IMatrix | ✂ Yes
| DeepSeek-Coder-V2-Instruct.Q4_K_S | Q4_K_S | - | ⏳ Processing | 🟢 IMatrix | -
| DeepSeek-Coder-V2-Instruct.IQ4_NL | IQ4_NL | - | ⏳ Processing | 🟢 IMatrix | -
| DeepSeek-Coder-V2-Instruct.IQ4_XS | IQ4_XS | - | ⏳ Processing | 🟢 IMatrix | -
| DeepSeek-Coder-V2-Instruct.Q3_K | Q3_K | - | ⏳ Processing | 🟢 IMatrix | -
| DeepSeek-Coder-V2-Instruct.Q3_K_L | Q3_K_L | - | ⏳ Processing | 🟢 IMatrix | -
| DeepSeek-Coder-V2-Instruct.Q3_K_S | Q3_K_S | - | ⏳ Processing | 🟢 IMatrix | -
| DeepSeek-Coder-V2-Instruct.IQ3_M | IQ3_M | - | ⏳ Processing | 🟢 IMatrix | -
| DeepSeek-Coder-V2-Instruct.IQ3_S | IQ3_S | - | ⏳ Processing | 🟢 IMatrix | -
| DeepSeek-Coder-V2-Instruct.IQ3_XS | IQ3_XS | - | ⏳ Processing | 🟢 IMatrix | -
| DeepSeek-Coder-V2-Instruct.IQ3_XXS | IQ3_XXS | - | ⏳ Processing | 🟢 IMatrix | -
| DeepSeek-Coder-V2-Instruct.Q2_K | Q2_K | - | ⏳ Processing | 🟢 IMatrix | -
| DeepSeek-Coder-V2-Instruct.Q2_K_S | Q2_K_S | - | ⏳ Processing | 🟢 IMatrix | -
| DeepSeek-Coder-V2-Instruct.IQ2_M | IQ2_M | - | ⏳ Processing | 🟢 IMatrix | -
| DeepSeek-Coder-V2-Instruct.IQ2_S | IQ2_S | - | ⏳ Processing | 🟢 IMatrix | -
| DeepSeek-Coder-V2-Instruct.IQ2_XS | IQ2_XS | - | ⏳ Processing | 🟢 IMatrix | -
| DeepSeek-Coder-V2-Instruct.IQ2_XXS | IQ2_XXS | - | ⏳ Processing | 🟢 IMatrix | -
| DeepSeek-Coder-V2-Instruct.IQ1_M | IQ1_M | - | ⏳ Processing | 🟢 IMatrix | -
| DeepSeek-Coder-V2-Instruct.IQ1_S | IQ1_S | - | ⏳ Processing | 🟢 IMatrix | -
## Downloading using huggingface-cli
If you do not have hugginface-cli installed:
```
pip install -U "huggingface_hub[cli]"
```
Download the specific file you want:
```
huggingface-cli download legraphista/DeepSeek-Coder-V2-Instruct-IMat-GGUF --include "DeepSeek-Coder-V2-Instruct.Q6_K.gguf" --local-dir ./
```
If the model file is big, it has been split into multiple files. In order to download them all to a local folder, run:
```
huggingface-cli download legraphista/DeepSeek-Coder-V2-Instruct-IMat-GGUF --include "DeepSeek-Coder-V2-Instruct.Q6_K/*" --local-dir ./
# see FAQ for merging GGUF's
```
---
## Inference
### Simple chat template
```
<｜begin▁of▁sentence｜>User: {user_prompt}
Assistant: {assistant_response}<｜end▁of▁sentence｜>User: {next_user_prompt}
```
### Chat template with system prompt
```
<｜begin▁of▁sentence｜>{system_prompt}
User: {user_prompt}
Assistant: {assistant_response}<｜end▁of▁sentence｜>User: {next_user_prompt}
```
### Llama.cpp
```
llama.cpp/main -m DeepSeek-Coder-V2-Instruct.Q6_K.gguf --color -i -p "prompt here (according to the chat template)"
```
---
## FAQ
### Why is the IMatrix not applied everywhere?
According to [this investigation](https://www.reddit.com/r/LocalLLaMA/comments/1993iro/ggufs_quants_can_punch_above_their_weights_now/), it appears that lower quantizations are the only ones that benefit from the imatrix input (as per hellaswag results).
### How do I merge a split GGUF?
1. Make sure you have `gguf-split` available
- To get hold of `gguf-split`, navigate to https://github.com/ggerganov/llama.cpp/releases
- Download the appropriate zip for your system from the latest release
- Unzip the archive and you should be able to find `gguf-split`
2. Locate your GGUF chunks folder (ex: `DeepSeek-Coder-V2-Instruct.Q6_K`)
3. Run `gguf-split --merge DeepSeek-Coder-V2-Instruct.Q6_K/DeepSeek-Coder-V2-Instruct.Q6_K-00001-of-XXXXX.gguf DeepSeek-Coder-V2-Instruct.Q6_K.gguf`
- Make sure to point `gguf-split` to the first chunk of the split.
---
Got a suggestion? Ping me [@legraphista](https://x.com/legraphista)! |