Duplicate from bartowski/codegemma-7b-it-GGUF

.gitattributes

@@ -0,0 +1,58 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz 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
+codegemma-7b-it-IQ1_M.gguf filter=lfs diff=lfs merge=lfs -text
+codegemma-7b-it-IQ1_S.gguf filter=lfs diff=lfs merge=lfs -text
+codegemma-7b-it-IQ2_M.gguf filter=lfs diff=lfs merge=lfs -text
+codegemma-7b-it-IQ2_S.gguf filter=lfs diff=lfs merge=lfs -text
+codegemma-7b-it-IQ2_XS.gguf filter=lfs diff=lfs merge=lfs -text
+codegemma-7b-it-IQ2_XXS.gguf filter=lfs diff=lfs merge=lfs -text
+codegemma-7b-it-IQ3_M.gguf filter=lfs diff=lfs merge=lfs -text
+codegemma-7b-it-IQ3_S.gguf filter=lfs diff=lfs merge=lfs -text
+codegemma-7b-it-IQ3_XS.gguf filter=lfs diff=lfs merge=lfs -text
+codegemma-7b-it-IQ3_XXS.gguf filter=lfs diff=lfs merge=lfs -text
+codegemma-7b-it-IQ4_NL.gguf filter=lfs diff=lfs merge=lfs -text
+codegemma-7b-it-IQ4_XS.gguf filter=lfs diff=lfs merge=lfs -text
+codegemma-7b-it-Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
+codegemma-7b-it-Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
+codegemma-7b-it-Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+codegemma-7b-it-Q3_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+codegemma-7b-it-Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+codegemma-7b-it-Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+codegemma-7b-it-Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+codegemma-7b-it-Q5_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+codegemma-7b-it-Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
+codegemma-7b-it-Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
+codegemma-7b-it.imatrix filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,93 @@
+---
+library_name: transformers
+extra_gated_heading: Access Gemma on Hugging Face
+extra_gated_prompt: >-
+  To access CodeGemma 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
+pipeline_tag: text-generation
+widget:
+- text: >
+    <start_of_turn>user
+    Write a Python function to calculate the nth fibonacci number.<end_of_turn>
+    <start_of_turn>model
+inference:
+  parameters:
+    max_new_tokens: 200
+license: gemma
+license_link: https://ai.google.dev/gemma/terms
+quantized_by: bartowski
+---
+
+## Llamacpp Quantizations of codegemma-7b-it
+
+Using <a href="https://github.com/ggerganov/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggerganov/llama.cpp/releases/tag/b2589">b2589</a> for quantization.
+
+Original model: https://huggingface.co/google/codegemma-7b-it
+
+All quants made using imatrix option with dataset provided by Kalomaze [here](https://github.com/ggerganov/llama.cpp/discussions/5263#discussioncomment-8395384)
+
+## Prompt format
+
+```
+<bos><start_of_turn>user
+{prompt}<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 |
+| -------- | ---------- | --------- | ----------- |
+| [codegemma-7b-it-Q8_0.gguf](https://huggingface.co/bartowski/codegemma-7b-it-GGUF/blob/main/codegemma-7b-it-Q8_0.gguf) | Q8_0 | 9.07GB | Extremely high quality, generally unneeded but max available quant. |
+| [codegemma-7b-it-Q6_K.gguf](https://huggingface.co/bartowski/codegemma-7b-it-GGUF/blob/main/codegemma-7b-it-Q6_K.gguf) | Q6_K | 7.01GB | Very high quality, near perfect, *recommended*. |
+| [codegemma-7b-it-Q5_K_M.gguf](https://huggingface.co/bartowski/codegemma-7b-it-GGUF/blob/main/codegemma-7b-it-Q5_K_M.gguf) | Q5_K_M | 6.14GB | High quality, *recommended*. |
+| [codegemma-7b-it-Q5_K_S.gguf](https://huggingface.co/bartowski/codegemma-7b-it-GGUF/blob/main/codegemma-7b-it-Q5_K_S.gguf) | Q5_K_S | 5.98GB | High quality, *recommended*. |
+| [codegemma-7b-it-Q4_K_M.gguf](https://huggingface.co/bartowski/codegemma-7b-it-GGUF/blob/main/codegemma-7b-it-Q4_K_M.gguf) | Q4_K_M | 5.32GB | Good quality, uses about 4.83 bits per weight, *recommended*. |
+| [codegemma-7b-it-Q4_K_S.gguf](https://huggingface.co/bartowski/codegemma-7b-it-GGUF/blob/main/codegemma-7b-it-Q4_K_S.gguf) | Q4_K_S | 5.04GB | Slightly lower quality with more space savings, *recommended*. |
+| [codegemma-7b-it-IQ4_NL.gguf](https://huggingface.co/bartowski/codegemma-7b-it-GGUF/blob/main/codegemma-7b-it-IQ4_NL.gguf) | IQ4_NL | 5.01GB | Decent quality, slightly smaller than Q4_K_S with similar performance *recommended*. |
+| [codegemma-7b-it-IQ4_XS.gguf](https://huggingface.co/bartowski/codegemma-7b-it-GGUF/blob/main/codegemma-7b-it-IQ4_XS.gguf) | IQ4_XS | 4.76GB | Decent quality, smaller than Q4_K_S with similar performance, *recommended*. |
+| [codegemma-7b-it-Q3_K_L.gguf](https://huggingface.co/bartowski/codegemma-7b-it-GGUF/blob/main/codegemma-7b-it-Q3_K_L.gguf) | Q3_K_L | 4.70GB | Lower quality but usable, good for low RAM availability. |
+| [codegemma-7b-it-Q3_K_M.gguf](https://huggingface.co/bartowski/codegemma-7b-it-GGUF/blob/main/codegemma-7b-it-Q3_K_M.gguf) | Q3_K_M | 4.36GB | Even lower quality. |
+| [codegemma-7b-it-IQ3_M.gguf](https://huggingface.co/bartowski/codegemma-7b-it-GGUF/blob/main/codegemma-7b-it-IQ3_M.gguf) | IQ3_M | 4.10GB | Medium-low quality, new method with decent performance comparable to Q3_K_M. |
+| [codegemma-7b-it-IQ3_S.gguf](https://huggingface.co/bartowski/codegemma-7b-it-GGUF/blob/main/codegemma-7b-it-IQ3_S.gguf) | IQ3_S | 3.98GB | Lower quality, new method with decent performance, recommended over Q3_K_S quant, same size with better performance. |
+| [codegemma-7b-it-Q3_K_S.gguf](https://huggingface.co/bartowski/codegemma-7b-it-GGUF/blob/main/codegemma-7b-it-Q3_K_S.gguf) | Q3_K_S | 3.98GB | Low quality, not recommended. |
+| [codegemma-7b-it-IQ3_XS.gguf](https://huggingface.co/bartowski/codegemma-7b-it-GGUF/blob/main/codegemma-7b-it-IQ3_XS.gguf) | IQ3_XS | 3.80GB | Lower quality, new method with decent performance, slightly better than Q3_K_S. |
+| [codegemma-7b-it-IQ3_XXS.gguf](https://huggingface.co/bartowski/codegemma-7b-it-GGUF/blob/main/codegemma-7b-it-IQ3_XXS.gguf) | IQ3_XXS | 3.48GB | Lower quality, new method with decent performance, comparable to Q3 quants. |
+| [codegemma-7b-it-Q2_K.gguf](https://huggingface.co/bartowski/codegemma-7b-it-GGUF/blob/main/codegemma-7b-it-Q2_K.gguf) | Q2_K | 3.48GB | Very low quality but surprisingly usable. |
+| [codegemma-7b-it-IQ2_M.gguf](https://huggingface.co/bartowski/codegemma-7b-it-GGUF/blob/main/codegemma-7b-it-IQ2_M.gguf) | IQ2_M | 3.13GB | Very low quality, uses SOTA techniques to also be surprisingly usable. |
+| [codegemma-7b-it-IQ2_S.gguf](https://huggingface.co/bartowski/codegemma-7b-it-GGUF/blob/main/codegemma-7b-it-IQ2_S.gguf) | IQ2_S | 2.91GB | Very low quality, uses SOTA techniques to be usable. |
+| [codegemma-7b-it-IQ2_XS.gguf](https://huggingface.co/bartowski/codegemma-7b-it-GGUF/blob/main/codegemma-7b-it-IQ2_XS.gguf) | IQ2_XS | 2.81GB | Very low quality, uses SOTA techniques to be usable. |
+| [codegemma-7b-it-IQ2_XXS.gguf](https://huggingface.co/bartowski/codegemma-7b-it-GGUF/blob/main/codegemma-7b-it-IQ2_XXS.gguf) | IQ2_XXS | 2.58GB | Lower quality, uses SOTA techniques to be usable. |
+| [codegemma-7b-it-IQ1_M.gguf](https://huggingface.co/bartowski/codegemma-7b-it-GGUF/blob/main/codegemma-7b-it-IQ1_M.gguf) | IQ1_M | 2.32GB | Extremely low quality, *not* recommended. |
+| [codegemma-7b-it-IQ1_S.gguf](https://huggingface.co/bartowski/codegemma-7b-it-GGUF/blob/main/codegemma-7b-it-IQ1_S.gguf) | IQ1_S | 2.16GB | Extremely low quality, *not* recommended. |
+
+## 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

codegemma-7b-it-IQ1_M.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c940e2826d89d18afaf50adb5e3fbc159b20f7e095f92a743a139167d78797ac
+size 2320034816

codegemma-7b-it-IQ1_S.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:189dd1ea07accbef9d0c61947226573856c622646c231aee93ad553abecf45f0
+size 2160192512

codegemma-7b-it-IQ2_M.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3597411048f86712d0f8f6e36330f4fa3e1ed7aa7f56639ab1478126426c10da
+size 3132025856

codegemma-7b-it-IQ2_S.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:76b2eb81b5660012355bf9b2091ed47d0280248100bc28f1fc33a435067a40f3
+size 2918902784

codegemma-7b-it-IQ2_XS.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cddd4fcf2eed7fbbe2323bb29a677c290f01a1a176864b32bf02d40842b0d82b
+size 2810571776

codegemma-7b-it-IQ2_XXS.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7b8200b5dcbcf80b67dec553e90cc5e58915a94765e61081640ff8235bde4d24
+size 2586438656

codegemma-7b-it-IQ3_M.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a2e0c1db54709525b3a95a9ed115b7d5786ff9337f7304ae72dbb830eeb1a7f4
+size 4106071040

codegemma-7b-it-IQ3_S.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d9c4fa059f4b5b2481c86a9561aa4f7aaed12aa8a7be62b83d6096c01c68c01a
+size 3982404608

codegemma-7b-it-IQ3_XS.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bfd9d073328c7c3c5ecac3de735635ce7500e9cda8b5d2110f0a1580100fb7f9
+size 3800738816

codegemma-7b-it-IQ3_XXS.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:94648d46ba932a258033f00df0d23c4baf8f03015dca52d201069eb98936c506
+size 3487099904

codegemma-7b-it-IQ4_NL.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7e5d17f30110452b424f705293f3f2321aea56d86e614c92809626bea5a66da4
+size 5011844096

codegemma-7b-it-IQ4_XS.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d2479d6ea71d40428434f93fd30ccf9a30e914fd1e394aa25a1befeada912ba6
+size 4769623040

codegemma-7b-it-Q2_K.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9d0914774f4198f323b8af5233d8481aab6a7a1c103ab22ee97f3029058458af
+size 3481447424

codegemma-7b-it-Q3_K_L.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:05643518c6e98d940d257e8a224a5f39badb94bf6373cfa56c6163aeec9acca8
+size 4709067776

codegemma-7b-it-Q3_K_M.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c23f2b814f479352b870f3d29ee83b63cf4e6d76e4b1da80e1d311b347b12a0e
+size 4369329152

codegemma-7b-it-Q3_K_S.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5fe476310d00d39e02bdde56874c33934e6f176b1af0a382e3e53f2d55483b09
+size 3982404608

codegemma-7b-it-Q4_K_M.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:71acf09271bd521ee11811d9c463781fdad49b202e6a72b22c816a0d0c6c1a6b
+size 5329759232

codegemma-7b-it-Q4_K_S.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:74e639180addf9af402ecc6e8c300d85efe62fc274cbb3f5800993909bfbad52
+size 5046447104

codegemma-7b-it-Q5_K_M.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4dbe3ff3be7b1ae0b6c15c3c7e56bd75e4dd9f73fdd299d06b284ca409dc0d17
+size 6144502784

codegemma-7b-it-Q5_K_S.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ff184846246e228e71d80162bc9c27ade06de5a5fd19205fff75ae8f6d511bfb
+size 5980728320

codegemma-7b-it-Q6_K.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5815a702cdff28c6170c93cc8c2de339490ec08773bd275671c41a3506ac55dc
+size 7010167808

codegemma-7b-it-Q8_0.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:20b20ee7b4265a5872bd58d669c394206f50418f3523b47563c9b1d4a78f37cb
+size 9077844992

codegemma-7b-it.imatrix

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:944f6da4e8af346df23d31e811aef3d70b117180b09e6a94c85d93f49649c465
+size 4938042