Llamacpp quants

.gitattributes

@@ -33,3 +33,22 @@ 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
+Qwen2-7B-Instruct-deccp-IQ2_M.gguf filter=lfs diff=lfs merge=lfs -text
+Qwen2-7B-Instruct-deccp-IQ2_S.gguf filter=lfs diff=lfs merge=lfs -text
+Qwen2-7B-Instruct-deccp-IQ2_XS.gguf filter=lfs diff=lfs merge=lfs -text
+Qwen2-7B-Instruct-deccp-IQ3_M.gguf filter=lfs diff=lfs merge=lfs -text
+Qwen2-7B-Instruct-deccp-IQ3_XS.gguf filter=lfs diff=lfs merge=lfs -text
+Qwen2-7B-Instruct-deccp-IQ3_XXS.gguf filter=lfs diff=lfs merge=lfs -text
+Qwen2-7B-Instruct-deccp-IQ4_XS.gguf filter=lfs diff=lfs merge=lfs -text
+Qwen2-7B-Instruct-deccp-Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
+Qwen2-7B-Instruct-deccp-Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
+Qwen2-7B-Instruct-deccp-Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+Qwen2-7B-Instruct-deccp-Q3_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+Qwen2-7B-Instruct-deccp-Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+Qwen2-7B-Instruct-deccp-Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+Qwen2-7B-Instruct-deccp-Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+Qwen2-7B-Instruct-deccp-Q5_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+Qwen2-7B-Instruct-deccp-Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
+Qwen2-7B-Instruct-deccp-Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
+Qwen2-7B-Instruct-deccp-f32.gguf filter=lfs diff=lfs merge=lfs -text
+Qwen2-7B-Instruct-deccp.imatrix filter=lfs diff=lfs merge=lfs -text

Qwen2-7B-Instruct-deccp-IQ2_M.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:303ee2dc98945d596b9461a253433012ba26fd78fa7dab9aaaf822ea8b55407f
+size 2780340032

Qwen2-7B-Instruct-deccp-IQ2_S.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5e1d53ac41ba443305389cde53c6e5fcfc46178b5cc3c5240ea0906875209b8c
+size 2595635008

Qwen2-7B-Instruct-deccp-IQ2_XS.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4f82b4cf6a5aa42ee3ae1cbb8e238dfde54f83aa176fddfd41dd4c466708ca46
+size 2469019456

Qwen2-7B-Instruct-deccp-IQ3_M.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:451771fbab200a1c05cca65b5fdb030b454fcb344689c139e11e0cf97c3e8a22
+size 3574009664

Qwen2-7B-Instruct-deccp-IQ3_XS.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cf7c45b87b3f4008f3b9461b6d0d71fff3edfdfa43ac71e15b3350a721a5bc0f
+size 3346253632

Qwen2-7B-Instruct-deccp-IQ3_XXS.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f7c26bcd9c716d612cba8bb7540d53a7dd1ff4d7017e5a4301772329e4cfa3c0
+size 3114512192

Qwen2-7B-Instruct-deccp-IQ4_XS.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6ac6beccf0152fa587ad5e436ee84274aa6fe5ae9e2398b506512844698d3269
+size 4218470208

Qwen2-7B-Instruct-deccp-Q2_K.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:86e386b9eb014c1b044e28bb7103b94332b1e841e6b67dfb06f2660d90817763
+size 3015937856

Qwen2-7B-Instruct-deccp-Q3_K_L.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fe09927a54f08e0196c92fe675091956c53573d25d3b4748137c1686852fb02b
+size 4088457024

Qwen2-7B-Instruct-deccp-Q3_K_M.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:72855fe97c26482c0eb47224f75b3daef9adae554a11eeda8e2cdb2959758b5f
+size 3808388928

Qwen2-7B-Instruct-deccp-Q3_K_S.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:426001b33c6e733458e136c60b06c4c28e6ded091ebf6cdf2ee77ab8c8e28ba3
+size 3492366144

Qwen2-7B-Instruct-deccp-Q4_K_M.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:af33abf330a53e9223490f6bbc8fb7ba93566055ce78af19e4cef669962dd2d2
+size 4683071296

Qwen2-7B-Instruct-deccp-Q4_K_S.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:67ec271d3111f80b888eb03a137cca5c97c1841bcfd7e0bfbde5968259744e32
+size 4457766720

Qwen2-7B-Instruct-deccp-Q5_K_M.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:982733960aafd9869fbd4582d154ee0dd2569ebfa6e645f0edea3bf941880b81
+size 5444828992

Qwen2-7B-Instruct-deccp-Q5_K_S.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d73ca87c40ac2da1a13ac72e9edf87dc8bef1b275eb715ac1dce5cbd889a6eb9
+size 5315174208

Qwen2-7B-Instruct-deccp-Q6_K.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c8e81b783086a1e49de4362166860c22f41618e868c4fc4087d182d9876866d6
+size 6254196544

Qwen2-7B-Instruct-deccp-Q8_0.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:46486c0f886a54ef9ac74c6cb19717ddc605ed4820caa914f733f0d3c35fa21a
+size 8098522944

Qwen2-7B-Instruct-deccp-f32.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2a9d94309510c7c12a9d08fa339f305ce43749a651a5924e181d74f94c19e53d
+size 30468417056

Qwen2-7B-Instruct-deccp.imatrix

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:095382deacc19b44c4e557bec6c07c9a42f9b300f6d5be58e8c8b170f335dac0
+size 4536679

README.md

@@ -0,0 +1,100 @@
+---
+license: apache-2.0
+datasets:
+- augmxnt/deccp
+language:
+- en
+- zh
+base_model: Qwen/Qwen2-7B-Instruct
+quantized_by: bartowski
+pipeline_tag: text-generation
+---
+
+## Llamacpp imatrix Quantizations of Qwen2-7B-Instruct-deccp
+
+Using <a href="https://github.com/ggerganov/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggerganov/llama.cpp/releases/tag/b3086">b3086</a> for quantization.
+
+Original model: https://huggingface.co/augmxnt/Qwen2-7B-Instruct-deccp
+
+All quants made using imatrix option with dataset from [here](https://gist.github.com/bartowski1182/eb213dccb3571f863da82e99418f81e8)
+
+## Prompt format
+
+```
+<|im_start|>system
+{system_prompt}<|im_end|>
+<|im_start|>user
+{prompt}<|im_end|>
+<|im_start|>assistant
+
+```
+
+## Download a file (not the whole branch) from below:
+
+| Filename | Quant type | File Size | Description |
+| -------- | ---------- | --------- | ----------- |
+| [Qwen2-7B-Instruct-deccp-Q8_0.gguf](https://huggingface.co/bartowski/Qwen2-7B-Instruct-deccp-GGUF/blob/main/Qwen2-7B-Instruct-deccp-Q8_0.gguf) | Q8_0 | 8.09GB | Extremely high quality, generally unneeded but max available quant. |
+| [Qwen2-7B-Instruct-deccp-Q6_K.gguf](https://huggingface.co/bartowski/Qwen2-7B-Instruct-deccp-GGUF/blob/main/Qwen2-7B-Instruct-deccp-Q6_K.gguf) | Q6_K | 6.25GB | Very high quality, near perfect, *recommended*. |
+| [Qwen2-7B-Instruct-deccp-Q5_K_M.gguf](https://huggingface.co/bartowski/Qwen2-7B-Instruct-deccp-GGUF/blob/main/Qwen2-7B-Instruct-deccp-Q5_K_M.gguf) | Q5_K_M | 5.44GB | High quality, *recommended*. |
+| [Qwen2-7B-Instruct-deccp-Q5_K_S.gguf](https://huggingface.co/bartowski/Qwen2-7B-Instruct-deccp-GGUF/blob/main/Qwen2-7B-Instruct-deccp-Q5_K_S.gguf) | Q5_K_S | 5.31GB | High quality, *recommended*. |
+| [Qwen2-7B-Instruct-deccp-Q4_K_M.gguf](https://huggingface.co/bartowski/Qwen2-7B-Instruct-deccp-GGUF/blob/main/Qwen2-7B-Instruct-deccp-Q4_K_M.gguf) | Q4_K_M | 4.68GB | Good quality, uses about 4.83 bits per weight, *recommended*. |
+| [Qwen2-7B-Instruct-deccp-Q4_K_S.gguf](https://huggingface.co/bartowski/Qwen2-7B-Instruct-deccp-GGUF/blob/main/Qwen2-7B-Instruct-deccp-Q4_K_S.gguf) | Q4_K_S | 4.45GB | Slightly lower quality with more space savings, *recommended*. |
+| [Qwen2-7B-Instruct-deccp-IQ4_XS.gguf](https://huggingface.co/bartowski/Qwen2-7B-Instruct-deccp-GGUF/blob/main/Qwen2-7B-Instruct-deccp-IQ4_XS.gguf) | IQ4_XS | 4.21GB | Decent quality, smaller than Q4_K_S with similar performance, *recommended*. |
+| [Qwen2-7B-Instruct-deccp-Q3_K_L.gguf](https://huggingface.co/bartowski/Qwen2-7B-Instruct-deccp-GGUF/blob/main/Qwen2-7B-Instruct-deccp-Q3_K_L.gguf) | Q3_K_L | 4.08GB | Lower quality but usable, good for low RAM availability. |
+| [Qwen2-7B-Instruct-deccp-Q3_K_M.gguf](https://huggingface.co/bartowski/Qwen2-7B-Instruct-deccp-GGUF/blob/main/Qwen2-7B-Instruct-deccp-Q3_K_M.gguf) | Q3_K_M | 3.80GB | Even lower quality. |
+| [Qwen2-7B-Instruct-deccp-IQ3_M.gguf](https://huggingface.co/bartowski/Qwen2-7B-Instruct-deccp-GGUF/blob/main/Qwen2-7B-Instruct-deccp-IQ3_M.gguf) | IQ3_M | 3.57GB | Medium-low quality, new method with decent performance comparable to Q3_K_M. |
+| [Qwen2-7B-Instruct-deccp-Q3_K_S.gguf](https://huggingface.co/bartowski/Qwen2-7B-Instruct-deccp-GGUF/blob/main/Qwen2-7B-Instruct-deccp-Q3_K_S.gguf) | Q3_K_S | 3.49GB | Low quality, not recommended. |
+| [Qwen2-7B-Instruct-deccp-IQ3_XS.gguf](https://huggingface.co/bartowski/Qwen2-7B-Instruct-deccp-GGUF/blob/main/Qwen2-7B-Instruct-deccp-IQ3_XS.gguf) | IQ3_XS | 3.34GB | Lower quality, new method with decent performance, slightly better than Q3_K_S. |
+| [Qwen2-7B-Instruct-deccp-IQ3_XXS.gguf](https://huggingface.co/bartowski/Qwen2-7B-Instruct-deccp-GGUF/blob/main/Qwen2-7B-Instruct-deccp-IQ3_XXS.gguf) | IQ3_XXS | 3.11GB | Lower quality, new method with decent performance, comparable to Q3 quants. |
+| [Qwen2-7B-Instruct-deccp-Q2_K.gguf](https://huggingface.co/bartowski/Qwen2-7B-Instruct-deccp-GGUF/blob/main/Qwen2-7B-Instruct-deccp-Q2_K.gguf) | Q2_K | 3.01GB | Very low quality but surprisingly usable. |
+| [Qwen2-7B-Instruct-deccp-IQ2_M.gguf](https://huggingface.co/bartowski/Qwen2-7B-Instruct-deccp-GGUF/blob/main/Qwen2-7B-Instruct-deccp-IQ2_M.gguf) | IQ2_M | 2.78GB | Very low quality, uses SOTA techniques to also be surprisingly usable. |
+| [Qwen2-7B-Instruct-deccp-IQ2_S.gguf](https://huggingface.co/bartowski/Qwen2-7B-Instruct-deccp-GGUF/blob/main/Qwen2-7B-Instruct-deccp-IQ2_S.gguf) | IQ2_S | 2.59GB | Very low quality, uses SOTA techniques to be usable. |
+| [Qwen2-7B-Instruct-deccp-IQ2_XS.gguf](https://huggingface.co/bartowski/Qwen2-7B-Instruct-deccp-GGUF/blob/main/Qwen2-7B-Instruct-deccp-IQ2_XS.gguf) | IQ2_XS | 2.46GB | 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/Qwen2-7B-Instruct-deccp-GGUF --include "Qwen2-7B-Instruct-deccp-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/Qwen2-7B-Instruct-deccp-GGUF --include "Qwen2-7B-Instruct-deccp-Q8_0.gguf/*" --local-dir Qwen2-7B-Instruct-deccp-Q8_0
+```
+
+You can either specify a new local-dir (Qwen2-7B-Instruct-deccp-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