--- 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)!