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