Llamacpp quants

.gitattributes

@@ -33,3 +33,30 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+gemma-2-27b-it-IQ2_M.gguf filter=lfs diff=lfs merge=lfs -text
+gemma-2-27b-it-IQ2_S.gguf filter=lfs diff=lfs merge=lfs -text
+gemma-2-27b-it-IQ2_XS.gguf filter=lfs diff=lfs merge=lfs -text
+gemma-2-27b-it-IQ3_M.gguf filter=lfs diff=lfs merge=lfs -text
+gemma-2-27b-it-IQ3_XS.gguf filter=lfs diff=lfs merge=lfs -text
+gemma-2-27b-it-IQ3_XXS.gguf filter=lfs diff=lfs merge=lfs -text
+gemma-2-27b-it-IQ4_XS.gguf filter=lfs diff=lfs merge=lfs -text
+gemma-2-27b-it-Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
+gemma-2-27b-it-Q2_K_L.gguf filter=lfs diff=lfs merge=lfs -text
+gemma-2-27b-it-Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
+gemma-2-27b-it-Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+gemma-2-27b-it-Q3_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+gemma-2-27b-it-Q3_K_XL.gguf filter=lfs diff=lfs merge=lfs -text
+gemma-2-27b-it-Q4_K_L.gguf filter=lfs diff=lfs merge=lfs -text
+gemma-2-27b-it-Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+gemma-2-27b-it-Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+gemma-2-27b-it-Q5_K_L.gguf filter=lfs diff=lfs merge=lfs -text
+gemma-2-27b-it-Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+gemma-2-27b-it-Q5_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+gemma-2-27b-it-Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
+gemma-2-27b-it-Q6_K_L.gguf filter=lfs diff=lfs merge=lfs -text
+gemma-2-27b-it-Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
+gemma-2-27b-it-Q8_0_L.gguf filter=lfs diff=lfs merge=lfs -text
+gemma-2-27b-it-f32.gguf/gemma-2-27b-it-f32-00001-of-00003.gguf filter=lfs diff=lfs merge=lfs -text
+gemma-2-27b-it-f32.gguf/gemma-2-27b-it-f32-00002-of-00003.gguf filter=lfs diff=lfs merge=lfs -text
+gemma-2-27b-it-f32.gguf/gemma-2-27b-it-f32-00003-of-00003.gguf filter=lfs diff=lfs merge=lfs -text
+gemma-2-27b-it.imatrix filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,108 @@
+---
+license: gemma
+library_name: transformers
+pipeline_tag: text-generation
+extra_gated_heading: Access Gemma on Hugging Face
+extra_gated_prompt: >-
+  To access Gemma on Hugging Face, you’re required to review and agree to
+  Google’s usage license. To do this, please ensure you’re logged in to Hugging
+  Face and click below. Requests are processed immediately.
+extra_gated_button_content: Acknowledge license
+quantized_by: bartowski
+---
+
+## Llamacpp imatrix Quantizations of gemma-2-27b-it
+
+Using <a href="https://github.com/ggerganov/llama.cpp/">llama.cpp</a> PR <a href="https://github.com/ggerganov/llama.cpp/pull/8156">8156</a> for quantization.
+
+Original model: https://huggingface.co/google/gemma-2-27b-it
+
+All quants made using imatrix option with dataset from [here](https://gist.github.com/bartowski1182/eb213dccb3571f863da82e99418f81e8)
+
+## Prompt format
+
+```
+<bos><start_of_turn>user
+{prompt}<end_of_turn>
+<start_of_turn>model
+<end_of_turn>
+<start_of_turn>model
+
+```
+
+Note that this model does not support a System prompt.
+
+## Download a file (not the whole branch) from below:
+
+| Filename | Quant type | File Size | Description |
+| -------- | ---------- | --------- | ----------- |
+| [gemma-2-27b-it-Q8_0_L.gguf](https://huggingface.co/bartowski/gemma-2-27b-it-GGUF/blob/main/gemma-2-27b-it-Q8_1.gguf) | Q8_0_L | 30.04GB | *Experimental*, uses f16 for embed and output weights. Please provide any feedback of differences. Extremely high quality, generally unneeded but max available quant. |
+| [gemma-2-27b-it-Q8_0.gguf](https://huggingface.co/bartowski/gemma-2-27b-it-GGUF/blob/main/gemma-2-27b-it-Q8_0.gguf) | Q8_0 | 28.93GB | Extremely high quality, generally unneeded but max available quant. |
+| [gemma-2-27b-it-Q6_K_L.gguf](https://huggingface.co/bartowski/gemma-2-27b-it-GGUF/blob/main/gemma-2-27b-it-Q6_K_L.gguf) | Q6_K_L | 23.73GB | *Experimental*, uses f16 for embed and output weights. Please provide any feedback of differences. Very high quality, near perfect, *recommended*. |
+| [gemma-2-27b-it-Q6_K.gguf](https://huggingface.co/bartowski/gemma-2-27b-it-GGUF/blob/main/gemma-2-27b-it-Q6_K.gguf) | Q6_K | 22.34GB | Very high quality, near perfect, *recommended*. |
+| [gemma-2-27b-it-Q5_K_L.gguf](https://huggingface.co/bartowski/gemma-2-27b-it-GGUF/blob/main/gemma-2-27b-it-Q5_K_L.gguf) | Q5_K_L | 20.80GB | *Experimental*, uses f16 for embed and output weights. Please provide any feedback of differences. High quality, *recommended*. |
+| [gemma-2-27b-it-Q5_K_M.gguf](https://huggingface.co/bartowski/gemma-2-27b-it-GGUF/blob/main/gemma-2-27b-it-Q5_K_M.gguf) | Q5_K_M | 19.40GB | High quality, *recommended*. |
+| [gemma-2-27b-it-Q5_K_S.gguf](https://huggingface.co/bartowski/gemma-2-27b-it-GGUF/blob/main/gemma-2-27b-it-Q5_K_S.gguf) | Q5_K_S | 18.88GB | High quality, *recommended*. |
+| [gemma-2-27b-it-Q4_K_L.gguf](https://huggingface.co/bartowski/gemma-2-27b-it-GGUF/blob/main/gemma-2-27b-it-Q4_K_L.gguf) | Q4_K_L | 18.03GB | *Experimental*, uses f16 for embed and output weights. Please provide any feedback of differences. Good quality, uses about 4.83 bits per weight, *recommended*. |
+| [gemma-2-27b-it-Q4_K_M.gguf](https://huggingface.co/bartowski/gemma-2-27b-it-GGUF/blob/main/gemma-2-27b-it-Q4_K_M.gguf) | Q4_K_M | 16.64GB | Good quality, uses about 4.83 bits per weight, *recommended*. |
+| [gemma-2-27b-it-Q4_K_S.gguf](https://huggingface.co/bartowski/gemma-2-27b-it-GGUF/blob/main/gemma-2-27b-it-Q4_K_S.gguf) | Q4_K_S | 15.73GB | Slightly lower quality with more space savings, *recommended*. |
+| [gemma-2-27b-it-IQ4_XS.gguf](https://huggingface.co/bartowski/gemma-2-27b-it-GGUF/blob/main/gemma-2-27b-it-IQ4_XS.gguf) | IQ4_XS | 14.81GB | Decent quality, smaller than Q4_K_S with similar performance, *recommended*. |
+| [gemma-2-27b-it-Q3_K_XL.gguf](https://huggingface.co/bartowski/gemma-2-27b-it-GGUF/blob/main/gemma-2-27b-it-Q3_K_XL.gguf) | Q3_K_XL | 15.91GB | *Experimental*, uses f16 for embed and output weights. Please provide any feedback of differences. Lower quality but usable, good for low RAM availability. |
+| [gemma-2-27b-it-Q3_K_L.gguf](https://huggingface.co/bartowski/gemma-2-27b-it-GGUF/blob/main/gemma-2-27b-it-Q3_K_L.gguf) | Q3_K_L | 14.51GB | Lower quality but usable, good for low RAM availability. |
+| [gemma-2-27b-it-Q3_K_M.gguf](https://huggingface.co/bartowski/gemma-2-27b-it-GGUF/blob/main/gemma-2-27b-it-Q3_K_M.gguf) | Q3_K_M | 13.42GB | Even lower quality. |
+| [gemma-2-27b-it-IQ3_M.gguf](https://huggingface.co/bartowski/gemma-2-27b-it-GGUF/blob/main/gemma-2-27b-it-IQ3_M.gguf) | IQ3_M | 12.45GB | Medium-low quality, new method with decent performance comparable to Q3_K_M. |
+| [gemma-2-27b-it-Q3_K_S.gguf](https://huggingface.co/bartowski/gemma-2-27b-it-GGUF/blob/main/gemma-2-27b-it-Q3_K_S.gguf) | Q3_K_S | 12.16GB | Low quality, not recommended. |
+| [gemma-2-27b-it-IQ3_XS.gguf](https://huggingface.co/bartowski/gemma-2-27b-it-GGUF/blob/main/gemma-2-27b-it-IQ3_XS.gguf) | IQ3_XS | 11.55GB | Lower quality, new method with decent performance, slightly better than Q3_K_S. |
+| [gemma-2-27b-it-IQ3_XXS.gguf](https://huggingface.co/bartowski/gemma-2-27b-it-GGUF/blob/main/gemma-2-27b-it-IQ3_XXS.gguf) | IQ3_XXS | 10.75GB | Lower quality, new method with decent performance, comparable to Q3 quants. |
+| [gemma-2-27b-it-Q2_K.gguf](https://huggingface.co/bartowski/gemma-2-27b-it-GGUF/blob/main/gemma-2-27b-it-Q2_K.gguf) | Q2_K | 10.45GB | Very low quality but surprisingly usable. |
+| [gemma-2-27b-it-IQ2_M.gguf](https://huggingface.co/bartowski/gemma-2-27b-it-GGUF/blob/main/gemma-2-27b-it-IQ2_M.gguf) | IQ2_M | 9.39GB | Very low quality, uses SOTA techniques to also be surprisingly usable. |
+| [gemma-2-27b-it-IQ2_S.gguf](https://huggingface.co/bartowski/gemma-2-27b-it-GGUF/blob/main/gemma-2-27b-it-IQ2_S.gguf) | IQ2_S | 8.65GB | Very low quality, uses SOTA techniques to be usable. |
+| [gemma-2-27b-it-IQ2_XS.gguf](https://huggingface.co/bartowski/gemma-2-27b-it-GGUF/blob/main/gemma-2-27b-it-IQ2_XS.gguf) | IQ2_XS | 8.40GB | Very low quality, uses SOTA techniques to be usable. |
+
+## 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 bartowski/gemma-2-27b-it-GGUF --include "gemma-2-27b-it-Q4_K_M.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 bartowski/gemma-2-27b-it-GGUF --include "gemma-2-27b-it-Q8_0.gguf/*" --local-dir gemma-2-27b-it-Q8_0
+```
+
+You can either specify a new local-dir (gemma-2-27b-it-Q8_0) or download them all in place (./)
+
+## Which file should I choose?
+
+A great write up with charts showing various performances is provided by Artefact2 [here](https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9)
+
+The first thing to figure out is how big a model you can run. To do this, you'll need to figure out how much RAM and/or VRAM you have.
+
+If you want your model running as FAST as possible, you'll want to fit the whole thing on your GPU's VRAM. Aim for a quant with a file size 1-2GB smaller than your GPU's total VRAM.
+
+If you want the absolute maximum quality, add both your system RAM and your GPU's VRAM together, then similarly grab a quant with a file size 1-2GB Smaller than that total.
+
+Next, you'll need to decide if you want to use an 'I-quant' or a 'K-quant'.
+
+If you don't want to think too much, grab one of the K-quants. These are in format 'QX_K_X', like Q5_K_M.
+
+If you want to get more into the weeds, you can check out this extremely useful feature chart:
+
+[llama.cpp feature matrix](https://github.com/ggerganov/llama.cpp/wiki/Feature-matrix)
+
+But basically, if you're aiming for below Q4, and you're running cuBLAS (Nvidia) or rocBLAS (AMD), you should look towards the I-quants. These are in format IQX_X, like IQ3_M. These are newer and offer better performance for their size.
+
+These I-quants can also be used on CPU and Apple Metal, but will be slower than their K-quant equivalent, so speed vs performance is a tradeoff you'll have to decide.
+
+The I-quants are *not* compatible with Vulcan, which is also AMD, so if you have an AMD card double check if you're using the rocBLAS build or the Vulcan build. At the time of writing this, LM Studio has a preview with ROCm support, and other inference engines have specific builds for ROCm.
+
+Want to support my work? Visit my ko-fi page here: https://ko-fi.com/bartowski

gemma-2-27b-it-IQ2_M.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:210ba473aa5c402376fb2cc3a0aa64b08941edd62cfc4961f439945c7c7b9ab5
+size 9399287232

gemma-2-27b-it-IQ2_S.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ab27afe42f164ef25fae6eef20568ff526b22e288c1b945562e67dd7c6d80f8a
+size 8652570048

gemma-2-27b-it-IQ2_XS.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:77605be226eb01df5f0713bdb0d5cdf32ddef662242e56b7f97ab413c0767760
+size 8400125376

gemma-2-27b-it-IQ3_M.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8333450a4fa2465ea3db1602c9c4ab95df81a8f8bccb163497d9b81f9b8f5512
+size 12455317440

gemma-2-27b-it-IQ3_XS.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f71094993f91f96f30441fe777fc1ccd03d6351e82c2ee4d33139e58c6aad485
+size 11551117248

gemma-2-27b-it-IQ3_XXS.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b3afbd24429c11fc1a476c28902cc29d9d3050a8934ae06aca52c1dd5ef7683e
+size 10751163840

gemma-2-27b-it-IQ4_XS.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:243740a513b51a9bbe06ba23886fc16aa2af2358c9e4d528f3d7477cc5ba8b86
+size 14814908352

gemma-2-27b-it-Q2_K.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bbec921d5d38e2e70cc330f6c8dc6b778ba52d25d67c261ae72c17a602eee926
+size 10450063296

gemma-2-27b-it-Q2_K_L.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cb6ed1dd06b184ed66a2d5d6c709ee52a31efcf51621eae0a349adb3d5e56762
+size 11842375104

gemma-2-27b-it-Q3_K_L.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a4b3a4ce2ef7f54efae106e51997d244a636013b08e1a0362373f3b8cdd8d941
+size 14519848896

gemma-2-27b-it-Q3_K_M.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:87c449bf6bb9b63f9ac6565acfd74cccd66952d7977546fedce1d0401c825e56
+size 13425135552

gemma-2-27b-it-Q3_K_S.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:11a593e33fc1d5b07e78751c9056abbfd326cca8d80c4a7827488abdd9893a02
+size 12169547712

gemma-2-27b-it-Q3_K_XL.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:819c2a159aa7d0bb0157e1e59d8e81d71c4d9a6ce877e0534fa7152b94f3c66d
+size 15912160704

gemma-2-27b-it-Q4_K_L.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:43319ad31888314879be17087e27a1e1d6378e56a5189ddb6624e09283181990
+size 18038181312

gemma-2-27b-it-Q4_K_M.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e54e7b800d464af4fa9966020e4a1b1d386cd9346de2d851a7bfe7d0797c44c4
+size 16645869504

gemma-2-27b-it-Q4_K_S.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4bd22f4b682cf80703f2bbd56faaa4e7389e1c1515516520791d633981bf2baf
+size 15739752384

gemma-2-27b-it-Q5_K_L.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c18751b5a67c1fd769e6df604ce26ead3e2eab99a263d712314b2c07c6a41d88
+size 20800916928

gemma-2-27b-it-Q5_K_M.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:63e379a35a495349e3091ee83426fd4b28a3294629146549272896c5c0650683
+size 19408605120

gemma-2-27b-it-Q5_K_S.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:156cbe9e21cfc9703ffb8cf7f24405de3f8285119ed3c1c703a2902937700a17
+size 18884693952

gemma-2-27b-it-Q6_K.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d5b35c93ec98c64a2a36283f5e583b59b4fe16dce15290956704c91f051c5e1e
+size 22344011712

gemma-2-27b-it-Q6_K_L.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:480824ff171578d95673f443289586e4f3fe5f4e5e76d050765e9151cdf1aa0e
+size 23736323520

gemma-2-27b-it-Q8_0.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f9f6b7107c7e29dd227dcf4e0524b0f64cae33cbcf18d9952c0ee91aa3cf44c9
+size 28938018240

gemma-2-27b-it-Q8_0_L.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7f13c6df81fda56b2bf363b211473aae8c142d94547900663271dd45deb9f325
+size 30044491200

gemma-2-27b-it-f32.gguf/gemma-2-27b-it-f32-00001-of-00003.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:abbd11eea0b1ba6f0e1093930268e01397e514ab0e48eb509b2970558ca94b20
+size 39607950848

gemma-2-27b-it-f32.gguf/gemma-2-27b-it-f32-00002-of-00003.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:42b85bc7430a43dda0b558323b14460e0e2326bbee276143ccfcaabd5678207a
+size 39977250368

gemma-2-27b-it-f32.gguf/gemma-2-27b-it-f32-00003-of-00003.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4a1990ff17113151f8114854d605d2e012df9af64cf8063d56addefde1728893
+size 29331734880

gemma-2-27b-it.imatrix

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9e90f2ac6a11ab92242966156e976ac4dc8b73c35714b66e37445c474b270f74
+size 11786697