--- base_model: microsoft/Phi-3-mini-128k-instruct inference: false language: - en library_name: gguf license: mit license_link: https://huggingface.co/microsoft/Phi-3-mini-128k-instruct/resolve/main/LICENSE pipeline_tag: text-generation quantized_by: legraphista tags: - quantized - GGUF - imatrix - quantization - imat - imatrix - static --- # Phi-3-mini-128k-instruct-IMat-GGUF _Llama.cpp imatrix quantization of microsoft/Phi-3-mini-128k-instruct_ Original Model: [microsoft/Phi-3-mini-128k-instruct](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct) Original dtype: `BF16` (`bfloat16`) Quantized by: llama.cpp [b3003](https://github.com/ggerganov/llama.cpp/releases/tag/b3003) IMatrix dataset: [here](https://gist.githubusercontent.com/legraphista/d6d93f1a254bcfc58e0af3777eaec41e/raw/d380e7002cea4a51c33fffd47db851942754e7cc/imatrix.calibration.medium.raw) - [Phi-3-mini-128k-instruct-IMat-GGUF](#phi-3-mini-128k-instruct-imat-gguf) - [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) - [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/Phi-3-mini-128k-instruct-IMat-GGUF/blob/main/imatrix.dat) ### Common Quants | Filename | Quant type | File Size | Status | Uses IMatrix | Is Split | | -------- | ---------- | --------- | ------ | ------------ | -------- | | [Phi-3-mini-128k-instruct.Q8_0.gguf](https://huggingface.co/legraphista/Phi-3-mini-128k-instruct-IMat-GGUF/blob/main/Phi-3-mini-128k-instruct.Q8_0.gguf) | Q8_0 | 4.06GB | ✅ Available | ⚪ No | 📦 No | [Phi-3-mini-128k-instruct.Q6_K.gguf](https://huggingface.co/legraphista/Phi-3-mini-128k-instruct-IMat-GGUF/blob/main/Phi-3-mini-128k-instruct.Q6_K.gguf) | Q6_K | 3.14GB | ✅ Available | ⚪ No | 📦 No | [Phi-3-mini-128k-instruct.Q4_K.gguf](https://huggingface.co/legraphista/Phi-3-mini-128k-instruct-IMat-GGUF/blob/main/Phi-3-mini-128k-instruct.Q4_K.gguf) | Q4_K | 2.39GB | ✅ Available | 🟢 Yes | 📦 No | [Phi-3-mini-128k-instruct.Q3_K.gguf](https://huggingface.co/legraphista/Phi-3-mini-128k-instruct-IMat-GGUF/blob/main/Phi-3-mini-128k-instruct.Q3_K.gguf) | Q3_K | 1.96GB | ✅ Available | 🟢 Yes | 📦 No | [Phi-3-mini-128k-instruct.Q2_K.gguf](https://huggingface.co/legraphista/Phi-3-mini-128k-instruct-IMat-GGUF/blob/main/Phi-3-mini-128k-instruct.Q2_K.gguf) | Q2_K | 1.42GB | ✅ Available | 🟢 Yes | 📦 No ### All Quants | Filename | Quant type | File Size | Status | Uses IMatrix | Is Split | | -------- | ---------- | --------- | ------ | ------------ | -------- | | [Phi-3-mini-128k-instruct.FP16.gguf](https://huggingface.co/legraphista/Phi-3-mini-128k-instruct-IMat-GGUF/blob/main/Phi-3-mini-128k-instruct.FP16.gguf) | F16 | 7.64GB | ✅ Available | ⚪ No | 📦 No | [Phi-3-mini-128k-instruct.BF16.gguf](https://huggingface.co/legraphista/Phi-3-mini-128k-instruct-IMat-GGUF/blob/main/Phi-3-mini-128k-instruct.BF16.gguf) | BF16 | 7.64GB | ✅ Available | ⚪ No | 📦 No | [Phi-3-mini-128k-instruct.Q5_K.gguf](https://huggingface.co/legraphista/Phi-3-mini-128k-instruct-IMat-GGUF/blob/main/Phi-3-mini-128k-instruct.Q5_K.gguf) | Q5_K | 2.82GB | ✅ Available | ⚪ No | 📦 No | [Phi-3-mini-128k-instruct.Q5_K_S.gguf](https://huggingface.co/legraphista/Phi-3-mini-128k-instruct-IMat-GGUF/blob/main/Phi-3-mini-128k-instruct.Q5_K_S.gguf) | Q5_K_S | 2.64GB | ✅ Available | ⚪ No | 📦 No | [Phi-3-mini-128k-instruct.Q4_K_S.gguf](https://huggingface.co/legraphista/Phi-3-mini-128k-instruct-IMat-GGUF/blob/main/Phi-3-mini-128k-instruct.Q4_K_S.gguf) | Q4_K_S | 2.19GB | ✅ Available | 🟢 Yes | 📦 No | [Phi-3-mini-128k-instruct.Q3_K_L.gguf](https://huggingface.co/legraphista/Phi-3-mini-128k-instruct-IMat-GGUF/blob/main/Phi-3-mini-128k-instruct.Q3_K_L.gguf) | Q3_K_L | 2.09GB | ✅ Available | 🟢 Yes | 📦 No | [Phi-3-mini-128k-instruct.Q3_K_S.gguf](https://huggingface.co/legraphista/Phi-3-mini-128k-instruct-IMat-GGUF/blob/main/Phi-3-mini-128k-instruct.Q3_K_S.gguf) | Q3_K_S | 1.68GB | ✅ Available | 🟢 Yes | 📦 No | [Phi-3-mini-128k-instruct.Q2_K_S.gguf](https://huggingface.co/legraphista/Phi-3-mini-128k-instruct-IMat-GGUF/blob/main/Phi-3-mini-128k-instruct.Q2_K_S.gguf) | Q2_K_S | 1.33GB | ✅ Available | 🟢 Yes | 📦 No | [Phi-3-mini-128k-instruct.IQ4_NL.gguf](https://huggingface.co/legraphista/Phi-3-mini-128k-instruct-IMat-GGUF/blob/main/Phi-3-mini-128k-instruct.IQ4_NL.gguf) | IQ4_NL | 2.18GB | ✅ Available | 🟢 Yes | 📦 No | [Phi-3-mini-128k-instruct.IQ4_XS.gguf](https://huggingface.co/legraphista/Phi-3-mini-128k-instruct-IMat-GGUF/blob/main/Phi-3-mini-128k-instruct.IQ4_XS.gguf) | IQ4_XS | 2.06GB | ✅ Available | 🟢 Yes | 📦 No | [Phi-3-mini-128k-instruct.IQ3_M.gguf](https://huggingface.co/legraphista/Phi-3-mini-128k-instruct-IMat-GGUF/blob/main/Phi-3-mini-128k-instruct.IQ3_M.gguf) | IQ3_M | 1.86GB | ✅ Available | 🟢 Yes | 📦 No | [Phi-3-mini-128k-instruct.IQ3_S.gguf](https://huggingface.co/legraphista/Phi-3-mini-128k-instruct-IMat-GGUF/blob/main/Phi-3-mini-128k-instruct.IQ3_S.gguf) | IQ3_S | 1.68GB | ✅ Available | 🟢 Yes | 📦 No | [Phi-3-mini-128k-instruct.IQ3_XS.gguf](https://huggingface.co/legraphista/Phi-3-mini-128k-instruct-IMat-GGUF/blob/main/Phi-3-mini-128k-instruct.IQ3_XS.gguf) | IQ3_XS | 1.63GB | ✅ Available | 🟢 Yes | 📦 No | [Phi-3-mini-128k-instruct.IQ3_XXS.gguf](https://huggingface.co/legraphista/Phi-3-mini-128k-instruct-IMat-GGUF/blob/main/Phi-3-mini-128k-instruct.IQ3_XXS.gguf) | IQ3_XXS | 1.51GB | ✅ Available | 🟢 Yes | 📦 No | [Phi-3-mini-128k-instruct.IQ2_M.gguf](https://huggingface.co/legraphista/Phi-3-mini-128k-instruct-IMat-GGUF/blob/main/Phi-3-mini-128k-instruct.IQ2_M.gguf) | IQ2_M | 1.32GB | ✅ Available | 🟢 Yes | 📦 No | [Phi-3-mini-128k-instruct.IQ2_S.gguf](https://huggingface.co/legraphista/Phi-3-mini-128k-instruct-IMat-GGUF/blob/main/Phi-3-mini-128k-instruct.IQ2_S.gguf) | IQ2_S | 1.22GB | ✅ Available | 🟢 Yes | 📦 No | Phi-3-mini-128k-instruct.IQ2_XS | IQ2_XS | - | ⏳ Processing | 🟢 Yes | - | Phi-3-mini-128k-instruct.IQ2_XXS | IQ2_XXS | - | ⏳ Processing | 🟢 Yes | - | Phi-3-mini-128k-instruct.IQ1_M | IQ1_M | - | ⏳ Processing | 🟢 Yes | - | Phi-3-mini-128k-instruct.IQ1_S | IQ1_S | - | ⏳ Processing | 🟢 Yes | - ## 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/Phi-3-mini-128k-instruct-IMat-GGUF --include "Phi-3-mini-128k-instruct.Q8_0.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/Phi-3-mini-128k-instruct-IMat-GGUF --include "Phi-3-mini-128k-instruct.Q8_0/*" --local-dir Phi-3-mini-128k-instruct.Q8_0 # see FAQ for merging GGUF's ``` --- ## Inference ### Simple chat template ``` <|user|> Can you provide ways to eat combinations of bananas and dragonfruits?<|end|> <|assistant|> Sure! Here are some ways to eat bananas and dragonfruits together: 1. Banana and dragonfruit smoothie: Blend bananas and dragonfruits together with some milk and honey. 2. Banana and dragonfruit salad: Mix sliced bananas and dragonfruits together with some lemon juice and honey.<|end|> <|user|> What about solving an 2x + 3 = 7 equation?<|end|> <|assistant|> ``` ### Llama.cpp ``` llama.cpp/main -m Phi-3-mini-128k-instruct.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](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: `Phi-3-mini-128k-instruct.Q8_0`) 3. Run `gguf-split --merge Phi-3-mini-128k-instruct.Q8_0/Phi-3-mini-128k-instruct.Q8_0-00001-of-XXXXX.gguf Phi-3-mini-128k-instruct.Q8_0.gguf` - Make sure to point `gguf-split` to the first chunk of the split. --- Got a suggestion? Ping me [@legraphista](https://x.com/legraphista)!