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DeepSeek-V2-Lite-Chat-IMat-GGUF

Llama.cpp imatrix quantization of deepseek-ai/DeepSeek-V2-Lite-Chat

Original Model: deepseek-ai/DeepSeek-V2-Lite-Chat
Original dtype: BF16 (bfloat16)
Quantized by: llama.cpp fork PR 7519
IMatrix dataset: here


Files

IMatrix

Status: ✅ Available
Link: here

Common Quants

Filename Quant type File Size Status Uses IMatrix Is Split
DeepSeek-V2-Lite-Chat.Q8_0.gguf Q8_0 16.70GB ✅ Available ⚪ No 📦 No
DeepSeek-V2-Lite-Chat.Q6_K.gguf Q6_K 14.07GB ✅ Available ⚪ No 📦 No
DeepSeek-V2-Lite-Chat.Q4_K.gguf Q4_K 10.36GB ✅ Available 🟢 Yes 📦 No
DeepSeek-V2-Lite-Chat.Q3_K.gguf Q3_K 8.13GB ✅ Available 🟢 Yes 📦 No
DeepSeek-V2-Lite-Chat.Q2_K.gguf Q2_K 6.43GB ✅ Available 🟢 Yes 📦 No

All Quants

Filename Quant type File Size Status Uses IMatrix Is Split
DeepSeek-V2-Lite-Chat.FP16.gguf F16 31.42GB ✅ Available ⚪ No 📦 No
DeepSeek-V2-Lite-Chat.BF16.gguf BF16 31.42GB ✅ Available ⚪ No 📦 No
DeepSeek-V2-Lite-Chat.Q5_K.gguf Q5_K 11.85GB ✅ Available ⚪ No 📦 No
DeepSeek-V2-Lite-Chat.Q5_K_S.gguf Q5_K_S 11.14GB ✅ Available ⚪ No 📦 No
DeepSeek-V2-Lite-Chat.Q4_K_S.gguf Q4_K_S 9.53GB ✅ Available 🟢 Yes 📦 No
DeepSeek-V2-Lite-Chat.Q3_K_L.gguf Q3_K_L 8.46GB ✅ Available 🟢 Yes 📦 No
DeepSeek-V2-Lite-Chat.Q3_K_S.gguf Q3_K_S 7.49GB ✅ Available 🟢 Yes 📦 No
DeepSeek-V2-Lite-Chat.Q2_K_S.gguf Q2_K_S 6.46GB ✅ Available 🟢 Yes 📦 No
DeepSeek-V2-Lite-Chat.IQ4_NL.gguf IQ4_NL 8.91GB ✅ Available 🟢 Yes 📦 No
DeepSeek-V2-Lite-Chat.IQ4_XS.gguf IQ4_XS 8.57GB ✅ Available 🟢 Yes 📦 No
DeepSeek-V2-Lite-Chat.IQ3_M.gguf IQ3_M 7.55GB ✅ Available 🟢 Yes 📦 No
DeepSeek-V2-Lite-Chat.IQ3_S.gguf IQ3_S 7.49GB ✅ Available 🟢 Yes 📦 No
DeepSeek-V2-Lite-Chat.IQ3_XS.gguf IQ3_XS 7.12GB ✅ Available 🟢 Yes 📦 No
DeepSeek-V2-Lite-Chat.IQ3_XXS.gguf IQ3_XXS 6.96GB ✅ Available 🟢 Yes 📦 No
DeepSeek-V2-Lite-Chat.IQ2_M.gguf IQ2_M 6.33GB ✅ Available 🟢 Yes 📦 No
DeepSeek-V2-Lite-Chat.IQ2_S.gguf IQ2_S 6.01GB ✅ Available 🟢 Yes 📦 No
DeepSeek-V2-Lite-Chat.IQ2_XS.gguf IQ2_XS 5.97GB ✅ Available 🟢 Yes 📦 No
DeepSeek-V2-Lite-Chat.IQ2_XXS.gguf IQ2_XXS 5.64GB ✅ Available 🟢 Yes 📦 No
DeepSeek-V2-Lite-Chat.IQ1_M.gguf IQ1_M 5.24GB ✅ Available 🟢 Yes 📦 No
DeepSeek-V2-Lite-Chat.IQ1_S.gguf IQ1_S 4.99GB ✅ Available 🟢 Yes 📦 No

Downloading using huggingface-cli

First, make sure you have hugginface-cli installed:

pip install -U "huggingface_hub[cli]"

Then, you can target the specific file you want:

huggingface-cli download legraphista/DeepSeek-V2-Lite-Chat-IMat-GGUF --include "DeepSeek-V2-Lite-Chat.Q8_0.gguf" --local-dir ./

If the model is bigger than 50GB, it will have been split into multiple files. In order to download them all to a local folder, run:

huggingface-cli download legraphista/DeepSeek-V2-Lite-Chat-IMat-GGUF --include "DeepSeek-V2-Lite-Chat.Q8_0/*" --local-dir DeepSeek-V2-Lite-Chat.Q8_0
# see FAQ for merging GGUF's

Inference

Simple chat template

<|begin▁of▁sentence|>User: {user_message_1}

Assistant: {assistant_message_1}<|end▁of▁sentence|>User: {user_message_2}

Assistant:

Chat template with system prompt

<|begin▁of▁sentence|>{system_message}

User: {user_message_1}

Assistant: {assistant_message_1}<|end▁of▁sentence|>User: {user_message_2}

Assistant:

Llama.cpp

llama.cpp/main -m DeepSeek-V2-Lite-Chat.Q8_0.gguf --color -i -p "prompt here (according to the chat template)"

FAQ

Why is the IMatrix not applied everywhere?

According to this investigation, 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
  2. Locate your GGUF chunks folder (ex: DeepSeek-V2-Lite-Chat.Q8_0)
  3. Run gguf-split --merge DeepSeek-V2-Lite-Chat.Q8_0/DeepSeek-V2-Lite-Chat.Q8_0-00001-of-XXXXX.gguf DeepSeek-V2-Lite-Chat.Q8_0.gguf
    • Make sure to point gguf-split to the first chunk of the split.

Got a suggestion? Ping me @legraphista!

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