mradermacher/KCOMP-MASH-QA-GGUF
1
0
Fork 0
Code Issues Pull Requests Actions Projects Releases Wiki Activity

初始化项目，由ModelHub XC社区提供模型

Browse Source 
Model: mradermacher/KCOMP-MASH-QA-GGUF
Source: Original Platform
This commit is contained in:
ModelHub XC
2026-06-10 14:07:17 +08:00
commit 49578994a3
14 changed files with 152 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

47
.gitattributes vendored Normal file
View File

@@ -0,0 +1,47 @@
*.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
KCOMP-MASH-QA.IQ4_XS.gguf filter=lfs diff=lfs merge=lfs -text
KCOMP-MASH-QA.Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
KCOMP-MASH-QA.Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
KCOMP-MASH-QA.Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text
KCOMP-MASH-QA.Q3_K_S.gguf filter=lfs diff=lfs merge=lfs -text
KCOMP-MASH-QA.Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
KCOMP-MASH-QA.Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text
KCOMP-MASH-QA.Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
KCOMP-MASH-QA.Q5_K_S.gguf filter=lfs diff=lfs merge=lfs -text
KCOMP-MASH-QA.Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
KCOMP-MASH-QA.Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
KCOMP-MASH-QA.f16.gguf filter=lfs diff=lfs merge=lfs -text

3
KCOMP-MASH-QA.IQ4_XS.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:7055bbc7c34af0d627a56f3d093ab6c84d8a99010a2fccb2c7ab84ff15269a25
size 1501221920

3
KCOMP-MASH-QA.Q2_K.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:a47730cba604d748a820ff6a46f63b587360b12e7090f72d4ecc275e2f12d0d7
size 1157927968

3
KCOMP-MASH-QA.Q3_K_L.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:b7ccc909c1d57b1b63aec7d693c24386ee27162bd418cc64e8eb0ec1e181b3ab
size 1465594912

3
KCOMP-MASH-QA.Q3_K_M.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:cceffe08d5c86e4e3e75d10cfdc0e63b26a44f737a706614ff1879aa4b0d589f
size 1383805984

3
KCOMP-MASH-QA.Q3_K_S.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:94da35378c5234e66779f8b26a8fd15de783b8a4fec6bc2160bf0ccf863206db
size 1287984160

3
KCOMP-MASH-QA.Q4_K_M.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:905d4fb3de021c86cd59d12dbe47bba375b8aa5135804fd6594b1a6ab403bd39
size 1630266400

3
KCOMP-MASH-QA.Q4_K_S.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:5b8e7275de0b115de04bae9c793b060d3b655d335c2755b3953b5338e96d1b84
size 1559843872

3
KCOMP-MASH-QA.Q5_K_M.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:7ecd04456fbb4b70c27f3c9c7c62c9707d970e45a737896bfe4e16cbfe12178d
size 1839653920

3
KCOMP-MASH-QA.Q5_K_S.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:77d352aef9d6c341ca95af63f44e49b18d797a25c81f4e902569928ec7de2c33
size 1798919200

3
KCOMP-MASH-QA.Q6_K.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:563276c5887bf648e449dee3106675d2c8290d86dbde3e45205d7c2be58b38e9
size 2062128160

3
KCOMP-MASH-QA.Q8_0.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:4e758956f9dd88ad3288ef5284240071d0ee3561dcdcc3f5f2154d9b00f4205b
size 2669074432

3
KCOMP-MASH-QA.f16.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:70f0ea65ec57a704ae16d3bdd215a0216229e6084090cbf41d988c424608f010
size 5018543872

69
README.md Normal file
View File

@@ -0,0 +1,69 @@
---
base_model: jeonghuncho/KCOMP-MASH-QA
language:
- en
library_name: transformers
mradermacher:
readme_rev: 1
quantized_by: mradermacher
tags: []
---
## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
static quants of https://huggingface.co/jeonghuncho/KCOMP-MASH-QA
<!-- provided-files -->
***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#KCOMP-MASH-QA-GGUF).***
weighted/imatrix quants are available at https://huggingface.co/mradermacher/KCOMP-MASH-QA-i1-GGUF
## Usage
If you are unsure how to use GGUF files, refer to one of [TheBloke's
READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
more details, including on how to concatenate multi-part files.
## Provided Quants
(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
| Link | Type | Size/GB | Notes |
|:-----|:-----|--------:|:------|
| [GGUF](https://huggingface.co/mradermacher/KCOMP-MASH-QA-GGUF/resolve/main/KCOMP-MASH-QA.Q2_K.gguf) | Q2_K | 1.3 | |
| [GGUF](https://huggingface.co/mradermacher/KCOMP-MASH-QA-GGUF/resolve/main/KCOMP-MASH-QA.Q3_K_S.gguf) | Q3_K_S | 1.4 | |
| [GGUF](https://huggingface.co/mradermacher/KCOMP-MASH-QA-GGUF/resolve/main/KCOMP-MASH-QA.Q3_K_M.gguf) | Q3_K_M | 1.5 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/KCOMP-MASH-QA-GGUF/resolve/main/KCOMP-MASH-QA.Q3_K_L.gguf) | Q3_K_L | 1.6 | |
| [GGUF](https://huggingface.co/mradermacher/KCOMP-MASH-QA-GGUF/resolve/main/KCOMP-MASH-QA.IQ4_XS.gguf) | IQ4_XS | 1.6 | |
| [GGUF](https://huggingface.co/mradermacher/KCOMP-MASH-QA-GGUF/resolve/main/KCOMP-MASH-QA.Q4_K_S.gguf) | Q4_K_S | 1.7 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/KCOMP-MASH-QA-GGUF/resolve/main/KCOMP-MASH-QA.Q4_K_M.gguf) | Q4_K_M | 1.7 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/KCOMP-MASH-QA-GGUF/resolve/main/KCOMP-MASH-QA.Q5_K_S.gguf) | Q5_K_S | 1.9 | |
| [GGUF](https://huggingface.co/mradermacher/KCOMP-MASH-QA-GGUF/resolve/main/KCOMP-MASH-QA.Q5_K_M.gguf) | Q5_K_M | 1.9 | |
| [GGUF](https://huggingface.co/mradermacher/KCOMP-MASH-QA-GGUF/resolve/main/KCOMP-MASH-QA.Q6_K.gguf) | Q6_K | 2.2 | very good quality |
| [GGUF](https://huggingface.co/mradermacher/KCOMP-MASH-QA-GGUF/resolve/main/KCOMP-MASH-QA.Q8_0.gguf) | Q8_0 | 2.8 | fast, best quality |
| [GGUF](https://huggingface.co/mradermacher/KCOMP-MASH-QA-GGUF/resolve/main/KCOMP-MASH-QA.f16.gguf) | f16 | 5.1 | 16 bpw, overkill |
Here is a handy graph by ikawrakow comparing some lower-quality quant
types (lower is better):
![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)
And here are Artefact2's thoughts on the matter:
https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
## FAQ / Model Request
See https://huggingface.co/mradermacher/model_requests for some answers to
questions you might have and/or if you want some other model quantized.
## Thanks
I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
me use its servers and providing upgrades to my workstation to enable
this work in my free time.
<!-- end -->