bartowski/mrm8488_Qwen3-14B-ft-limo-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: bartowski/mrm8488_Qwen3-14B-ft-limo-GGUF
Source: Original Platform
This commit is contained in:
ModelHub XC
2026-09-04 03:16:12 +08:00
commit 9a886d0ec3
30 changed files with 309 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

49
.gitattributes vendored Normal file
View File

@@ -0,0 +1,49 @@
*.7z filter=lfs diff=lfs merge=lfs -text
*.arrow filter=lfs diff=lfs merge=lfs -text
*.bin filter=lfs diff=lfs merge=lfs -text
*.bin.* filter=lfs diff=lfs merge=lfs -text
*.bz2 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
*.model filter=lfs diff=lfs merge=lfs -text
*.msgpack 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
*.pt filter=lfs diff=lfs merge=lfs -text
*.pth filter=lfs diff=lfs merge=lfs -text
*.rar filter=lfs diff=lfs merge=lfs -text
saved_model/**/* 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
*.xz filter=lfs diff=lfs merge=lfs -text
*.zip filter=lfs diff=lfs merge=lfs -text
*.zstandard filter=lfs diff=lfs merge=lfs -text
*.tfevents* filter=lfs diff=lfs merge=lfs -text
*.db* filter=lfs diff=lfs merge=lfs -text
*.ark* filter=lfs diff=lfs merge=lfs -text
**/*ckpt*data* filter=lfs diff=lfs merge=lfs -text
**/*ckpt*.meta filter=lfs diff=lfs merge=lfs -text
**/*ckpt*.index filter=lfs diff=lfs merge=lfs -text
*.safetensors filter=lfs diff=lfs merge=lfs -text
*.ckpt filter=lfs diff=lfs merge=lfs -text
*.gguf* filter=lfs diff=lfs merge=lfs -text
*.ggml filter=lfs diff=lfs merge=lfs -text
*.llamafile* filter=lfs diff=lfs merge=lfs -text
*.pt2 filter=lfs diff=lfs merge=lfs -text
*.mlmodel filter=lfs diff=lfs merge=lfs -text
*.npy filter=lfs diff=lfs merge=lfs -text
*.npz filter=lfs diff=lfs merge=lfs -text
*.pickle filter=lfs diff=lfs merge=lfs -text
*.pkl filter=lfs diff=lfs merge=lfs -text
*.tar filter=lfs diff=lfs merge=lfs -text
*.wasm filter=lfs diff=lfs merge=lfs -text
*.zst filter=lfs diff=lfs merge=lfs -text
*tfevents* filter=lfs diff=lfs merge=lfs -text
mrm8488_Qwen3-14B-ft-limo.imatrix filter=lfs diff=lfs merge=lfs -text

178
README.md Normal file
View File

@@ -0,0 +1,178 @@
---
quantized_by: bartowski
pipeline_tag: text-generation
tags:
- limo
datasets:
- GAIR/LIMO
base_model: mrm8488/Qwen3-14B-ft-limo
thumbnail: https://huggingface.co/mrm8488/Qwen3-14B-ft-limo/resolve/main/logo-min.png
base_model_relation: quantized
license: apache-2.0
---
## Llamacpp imatrix Quantizations of Qwen3-14B-ft-limo by mrm8488
Using <a href="https://github.com/ggerganov/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggerganov/llama.cpp/releases/tag/b5490">b5490</a> for quantization.
Original model: https://huggingface.co/mrm8488/Qwen3-14B-ft-limo
All quants made using imatrix option with dataset from [here](https://gist.github.com/bartowski1182/eb213dccb3571f863da82e99418f81e8)
Run them in [LM Studio](https://lmstudio.ai/)
Run them directly with [llama.cpp](https://github.com/ggerganov/llama.cpp), or any other llama.cpp based project
## 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 | Split | Description |
| -------- | ---------- | --------- | ----- | ----------- |
| [Qwen3-14B-ft-limo-bf16.gguf](https://huggingface.co/bartowski/mrm8488_Qwen3-14B-ft-limo-GGUF/blob/main/mrm8488_Qwen3-14B-ft-limo-bf16.gguf) | bf16 | 29.54GB | false | Full BF16 weights. |
| [Qwen3-14B-ft-limo-Q8_0.gguf](https://huggingface.co/bartowski/mrm8488_Qwen3-14B-ft-limo-GGUF/blob/main/mrm8488_Qwen3-14B-ft-limo-Q8_0.gguf) | Q8_0 | 15.70GB | false | Extremely high quality, generally unneeded but max available quant. |
| [Qwen3-14B-ft-limo-Q6_K_L.gguf](https://huggingface.co/bartowski/mrm8488_Qwen3-14B-ft-limo-GGUF/blob/main/mrm8488_Qwen3-14B-ft-limo-Q6_K_L.gguf) | Q6_K_L | 12.50GB | false | Uses Q8_0 for embed and output weights. Very high quality, near perfect, *recommended*. |
| [Qwen3-14B-ft-limo-Q6_K.gguf](https://huggingface.co/bartowski/mrm8488_Qwen3-14B-ft-limo-GGUF/blob/main/mrm8488_Qwen3-14B-ft-limo-Q6_K.gguf) | Q6_K | 12.12GB | false | Very high quality, near perfect, *recommended*. |
| [Qwen3-14B-ft-limo-Q5_K_L.gguf](https://huggingface.co/bartowski/mrm8488_Qwen3-14B-ft-limo-GGUF/blob/main/mrm8488_Qwen3-14B-ft-limo-Q5_K_L.gguf) | Q5_K_L | 10.99GB | false | Uses Q8_0 for embed and output weights. High quality, *recommended*. |
| [Qwen3-14B-ft-limo-Q5_K_M.gguf](https://huggingface.co/bartowski/mrm8488_Qwen3-14B-ft-limo-GGUF/blob/main/mrm8488_Qwen3-14B-ft-limo-Q5_K_M.gguf) | Q5_K_M | 10.51GB | false | High quality, *recommended*. |
| [Qwen3-14B-ft-limo-Q5_K_S.gguf](https://huggingface.co/bartowski/mrm8488_Qwen3-14B-ft-limo-GGUF/blob/main/mrm8488_Qwen3-14B-ft-limo-Q5_K_S.gguf) | Q5_K_S | 10.26GB | false | High quality, *recommended*. |
| [Qwen3-14B-ft-limo-Q4_K_L.gguf](https://huggingface.co/bartowski/mrm8488_Qwen3-14B-ft-limo-GGUF/blob/main/mrm8488_Qwen3-14B-ft-limo-Q4_K_L.gguf) | Q4_K_L | 9.58GB | false | Uses Q8_0 for embed and output weights. Good quality, *recommended*. |
| [Qwen3-14B-ft-limo-Q4_1.gguf](https://huggingface.co/bartowski/mrm8488_Qwen3-14B-ft-limo-GGUF/blob/main/mrm8488_Qwen3-14B-ft-limo-Q4_1.gguf) | Q4_1 | 9.39GB | false | Legacy format, similar performance to Q4_K_S but with improved tokens/watt on Apple silicon. |
| [Qwen3-14B-ft-limo-Q4_K_M.gguf](https://huggingface.co/bartowski/mrm8488_Qwen3-14B-ft-limo-GGUF/blob/main/mrm8488_Qwen3-14B-ft-limo-Q4_K_M.gguf) | Q4_K_M | 9.00GB | false | Good quality, default size for most use cases, *recommended*. |
| [Qwen3-14B-ft-limo-Q3_K_XL.gguf](https://huggingface.co/bartowski/mrm8488_Qwen3-14B-ft-limo-GGUF/blob/main/mrm8488_Qwen3-14B-ft-limo-Q3_K_XL.gguf) | Q3_K_XL | 8.58GB | false | Uses Q8_0 for embed and output weights. Lower quality but usable, good for low RAM availability. |
| [Qwen3-14B-ft-limo-Q4_K_S.gguf](https://huggingface.co/bartowski/mrm8488_Qwen3-14B-ft-limo-GGUF/blob/main/mrm8488_Qwen3-14B-ft-limo-Q4_K_S.gguf) | Q4_K_S | 8.57GB | false | Slightly lower quality with more space savings, *recommended*. |
| [Qwen3-14B-ft-limo-Q4_0.gguf](https://huggingface.co/bartowski/mrm8488_Qwen3-14B-ft-limo-GGUF/blob/main/mrm8488_Qwen3-14B-ft-limo-Q4_0.gguf) | Q4_0 | 8.54GB | false | Legacy format, offers online repacking for ARM and AVX CPU inference. |
| [Qwen3-14B-ft-limo-IQ4_NL.gguf](https://huggingface.co/bartowski/mrm8488_Qwen3-14B-ft-limo-GGUF/blob/main/mrm8488_Qwen3-14B-ft-limo-IQ4_NL.gguf) | IQ4_NL | 8.54GB | false | Similar to IQ4_XS, but slightly larger. Offers online repacking for ARM CPU inference. |
| [Qwen3-14B-ft-limo-IQ4_XS.gguf](https://huggingface.co/bartowski/mrm8488_Qwen3-14B-ft-limo-GGUF/blob/main/mrm8488_Qwen3-14B-ft-limo-IQ4_XS.gguf) | IQ4_XS | 8.11GB | false | Decent quality, smaller than Q4_K_S with similar performance, *recommended*. |
| [Qwen3-14B-ft-limo-Q3_K_L.gguf](https://huggingface.co/bartowski/mrm8488_Qwen3-14B-ft-limo-GGUF/blob/main/mrm8488_Qwen3-14B-ft-limo-Q3_K_L.gguf) | Q3_K_L | 7.90GB | false | Lower quality but usable, good for low RAM availability. |
| [Qwen3-14B-ft-limo-Q3_K_M.gguf](https://huggingface.co/bartowski/mrm8488_Qwen3-14B-ft-limo-GGUF/blob/main/mrm8488_Qwen3-14B-ft-limo-Q3_K_M.gguf) | Q3_K_M | 7.32GB | false | Low quality. |
| [Qwen3-14B-ft-limo-IQ3_M.gguf](https://huggingface.co/bartowski/mrm8488_Qwen3-14B-ft-limo-GGUF/blob/main/mrm8488_Qwen3-14B-ft-limo-IQ3_M.gguf) | IQ3_M | 6.88GB | false | Medium-low quality, new method with decent performance comparable to Q3_K_M. |
| [Qwen3-14B-ft-limo-Q3_K_S.gguf](https://huggingface.co/bartowski/mrm8488_Qwen3-14B-ft-limo-GGUF/blob/main/mrm8488_Qwen3-14B-ft-limo-Q3_K_S.gguf) | Q3_K_S | 6.66GB | false | Low quality, not recommended. |
| [Qwen3-14B-ft-limo-Q2_K_L.gguf](https://huggingface.co/bartowski/mrm8488_Qwen3-14B-ft-limo-GGUF/blob/main/mrm8488_Qwen3-14B-ft-limo-Q2_K_L.gguf) | Q2_K_L | 6.51GB | false | Uses Q8_0 for embed and output weights. Very low quality but surprisingly usable. |
| [Qwen3-14B-ft-limo-IQ3_XS.gguf](https://huggingface.co/bartowski/mrm8488_Qwen3-14B-ft-limo-GGUF/blob/main/mrm8488_Qwen3-14B-ft-limo-IQ3_XS.gguf) | IQ3_XS | 6.38GB | false | Lower quality, new method with decent performance, slightly better than Q3_K_S. |
| [Qwen3-14B-ft-limo-IQ3_XXS.gguf](https://huggingface.co/bartowski/mrm8488_Qwen3-14B-ft-limo-GGUF/blob/main/mrm8488_Qwen3-14B-ft-limo-IQ3_XXS.gguf) | IQ3_XXS | 5.94GB | false | Lower quality, new method with decent performance, comparable to Q3 quants. |
| [Qwen3-14B-ft-limo-Q2_K.gguf](https://huggingface.co/bartowski/mrm8488_Qwen3-14B-ft-limo-GGUF/blob/main/mrm8488_Qwen3-14B-ft-limo-Q2_K.gguf) | Q2_K | 5.75GB | false | Very low quality but surprisingly usable. |
| [Qwen3-14B-ft-limo-IQ2_M.gguf](https://huggingface.co/bartowski/mrm8488_Qwen3-14B-ft-limo-GGUF/blob/main/mrm8488_Qwen3-14B-ft-limo-IQ2_M.gguf) | IQ2_M | 5.32GB | false | Relatively low quality, uses SOTA techniques to be surprisingly usable. |
| [Qwen3-14B-ft-limo-IQ2_S.gguf](https://huggingface.co/bartowski/mrm8488_Qwen3-14B-ft-limo-GGUF/blob/main/mrm8488_Qwen3-14B-ft-limo-IQ2_S.gguf) | IQ2_S | 4.96GB | false | Low quality, uses SOTA techniques to be usable. |
| [Qwen3-14B-ft-limo-IQ2_XS.gguf](https://huggingface.co/bartowski/mrm8488_Qwen3-14B-ft-limo-GGUF/blob/main/mrm8488_Qwen3-14B-ft-limo-IQ2_XS.gguf) | IQ2_XS | 4.69GB | false | Low quality, uses SOTA techniques to be usable. |
## Embed/output weights
Some of these quants (Q3_K_XL, Q4_K_L etc) are the standard quantization method with the embeddings and output weights quantized to Q8_0 instead of what they would normally default to.
## Downloading using huggingface-cli
<details>
<summary>Click to view download instructions</summary>
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/mrm8488_Qwen3-14B-ft-limo-GGUF --include "mrm8488_Qwen3-14B-ft-limo-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/mrm8488_Qwen3-14B-ft-limo-GGUF --include "mrm8488_Qwen3-14B-ft-limo-Q8_0/*" --local-dir ./
```
You can either specify a new local-dir (mrm8488_Qwen3-14B-ft-limo-Q8_0) or download them all in place (./)
</details>
## ARM/AVX information
Previously, you would download Q4_0_4_4/4_8/8_8, and these would have their weights interleaved in memory in order to improve performance on ARM and AVX machines by loading up more data in one pass.
Now, however, there is something called "online repacking" for weights. details in [this PR](https://github.com/ggerganov/llama.cpp/pull/9921). If you use Q4_0 and your hardware would benefit from repacking weights, it will do it automatically on the fly.
As of llama.cpp build [b4282](https://github.com/ggerganov/llama.cpp/releases/tag/b4282) you will not be able to run the Q4_0_X_X files and will instead need to use Q4_0.
Additionally, if you want to get slightly better quality for , you can use IQ4_NL thanks to [this PR](https://github.com/ggerganov/llama.cpp/pull/10541) which will also repack the weights for ARM, though only the 4_4 for now. The loading time may be slower but it will result in an overall speed incrase.
<details>
<summary>Click to view Q4_0_X_X information (deprecated</summary>
I'm keeping this section to show the potential theoretical uplift in performance from using the Q4_0 with online repacking.
<details>
<summary>Click to view benchmarks on an AVX2 system (EPYC7702)</summary>
| model | size | params | backend | threads | test | t/s | % (vs Q4_0) |
| ------------------------------ | ---------: | ---------: | ---------- | ------: | ------------: | -------------------: |-------------: |
| qwen2 3B Q4_0 | 1.70 GiB | 3.09 B | CPU | 64 | pp512 | 204.03 ± 1.03 | 100% |
| qwen2 3B Q4_0 | 1.70 GiB | 3.09 B | CPU | 64 | pp1024 | 282.92 ± 0.19 | 100% |
| qwen2 3B Q4_0 | 1.70 GiB | 3.09 B | CPU | 64 | pp2048 | 259.49 ± 0.44 | 100% |
| qwen2 3B Q4_0 | 1.70 GiB | 3.09 B | CPU | 64 | tg128 | 39.12 ± 0.27 | 100% |
| qwen2 3B Q4_0 | 1.70 GiB | 3.09 B | CPU | 64 | tg256 | 39.31 ± 0.69 | 100% |
| qwen2 3B Q4_0 | 1.70 GiB | 3.09 B | CPU | 64 | tg512 | 40.52 ± 0.03 | 100% |
| qwen2 3B Q4_K_M | 1.79 GiB | 3.09 B | CPU | 64 | pp512 | 301.02 ± 1.74 | 147% |
| qwen2 3B Q4_K_M | 1.79 GiB | 3.09 B | CPU | 64 | pp1024 | 287.23 ± 0.20 | 101% |
| qwen2 3B Q4_K_M | 1.79 GiB | 3.09 B | CPU | 64 | pp2048 | 262.77 ± 1.81 | 101% |
| qwen2 3B Q4_K_M | 1.79 GiB | 3.09 B | CPU | 64 | tg128 | 18.80 ± 0.99 | 48% |
| qwen2 3B Q4_K_M | 1.79 GiB | 3.09 B | CPU | 64 | tg256 | 24.46 ± 3.04 | 83% |
| qwen2 3B Q4_K_M | 1.79 GiB | 3.09 B | CPU | 64 | tg512 | 36.32 ± 3.59 | 90% |
| qwen2 3B Q4_0_8_8 | 1.69 GiB | 3.09 B | CPU | 64 | pp512 | 271.71 ± 3.53 | 133% |
| qwen2 3B Q4_0_8_8 | 1.69 GiB | 3.09 B | CPU | 64 | pp1024 | 279.86 ± 45.63 | 100% |
| qwen2 3B Q4_0_8_8 | 1.69 GiB | 3.09 B | CPU | 64 | pp2048 | 320.77 ± 5.00 | 124% |
| qwen2 3B Q4_0_8_8 | 1.69 GiB | 3.09 B | CPU | 64 | tg128 | 43.51 ± 0.05 | 111% |
| qwen2 3B Q4_0_8_8 | 1.69 GiB | 3.09 B | CPU | 64 | tg256 | 43.35 ± 0.09 | 110% |
| qwen2 3B Q4_0_8_8 | 1.69 GiB | 3.09 B | CPU | 64 | tg512 | 42.60 ± 0.31 | 105% |
Q4_0_8_8 offers a nice bump to prompt processing and a small bump to text generation
</details>
</details>
## Which file should I choose?
<details>
<summary>Click here for details</summary>
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, but will be slower than their K-quant equivalent, so speed vs performance is a tradeoff you'll have to decide.
</details>
## Credits
Thank you kalomaze and Dampf for assistance in creating the imatrix calibration dataset.
Thank you ZeroWw for the inspiration to experiment with embed/output.
Thank you to LM Studio for sponsoring my work.
Want to support my work? Visit my ko-fi page here: https://ko-fi.com/bartowski

1
configuration.json Normal file
View File

@@ -0,0 +1 @@
{"framework": "pytorch", "task": "text-generation", "allow_remote": true}

3
mrm8488_Qwen3-14B-ft-limo-IQ2_M.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:b98f574b8647ce535218be3e7b36332afa8260599021f7da40bbaa59b54c2440
size 5322942112

3
mrm8488_Qwen3-14B-ft-limo-IQ2_S.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:74e0f7f920c66de16e3e848c811a06d97c205384a5474fb7817ce55ab65c57b8
size 4963313312

3
mrm8488_Qwen3-14B-ft-limo-IQ2_XS.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:5ad5309d79224b875009dc9e22a206275c05f604c87facf86b53e206bbf11a26
size 4691589792

3
mrm8488_Qwen3-14B-ft-limo-IQ3_M.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:f17b558b1a30d871653fe80a73a1cb93e517f1a9fa687f74e8543ecba22732cb
size 6883410592

3
mrm8488_Qwen3-14B-ft-limo-IQ3_XS.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:e49277d93093f3b08c265bedd59dfd9b225b9a89bbec40483a29f42a42d114c7
size 6375301792

3
mrm8488_Qwen3-14B-ft-limo-IQ3_XXS.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:c75af3c5c7e687167f665da103ef5d00ac8c80b2c61ac34477c263aa29087509
size 5942666912

3
mrm8488_Qwen3-14B-ft-limo-IQ4_NL.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:d81c309acbf6e906e8aff793c38119a9f7ba038bda5d79438ab703ac31bcae0c
size 8541363872

3
mrm8488_Qwen3-14B-ft-limo-IQ4_XS.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:ae75d5574466800c775815e37fb6253cb83a3420ca391efcdee6bcfc0985198b
size 8110730912

3
mrm8488_Qwen3-14B-ft-limo-Q2_K.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:78bda35efa58eba25521b446c735fa52d98498bb9501cb09a8933d5a0b1384d6
size 5753984672

3
mrm8488_Qwen3-14B-ft-limo-Q2_K_L.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:b6070138e5268edd161a0d27581c621729706da89748e6ce067fa96919ecc8d4
size 6513664672

3
mrm8488_Qwen3-14B-ft-limo-Q3_K_L.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:689f4ee12d8c2c5eb374a4e29dea0ebdd9b688d7ce6407b2fcb24970fbf3508b
size 7900652192

3
mrm8488_Qwen3-14B-ft-limo-Q3_K_M.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:63e982bce79456cc6a7510492d0cc3489681baf2ab1efa3eb6339ccb24c0527a
size 7321313952

3
mrm8488_Qwen3-14B-ft-limo-Q3_K_S.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:bd4043b0d4d2ac6ac334ebdee82506e213859f8ef9f10032b1fe824938033385
size 6657106592

3
mrm8488_Qwen3-14B-ft-limo-Q3_K_XL.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:243c03ba504b1bddb0c4c6ef6684013a4b1268c1ff64b4d31abe1683088f6509
size 8581325472

3
mrm8488_Qwen3-14B-ft-limo-Q4_0.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:aa66924af9a094ad7cd0056d2da70e579e200fab58b005462e811c7f2823545f
size 8543002272

3
mrm8488_Qwen3-14B-ft-limo-Q4_1.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:77695d4c39dcb38498eb21cd1ab4004bc81c6bdf160fd03a5d107566fa32c758
size 9389522592

3
mrm8488_Qwen3-14B-ft-limo-Q4_K_L.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:6c53e28ad5dbada4921703015acb5852c4565d0d16be4239545e645ffe61f291
size 9579111072

3
mrm8488_Qwen3-14B-ft-limo-Q4_K_M.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:19d6dfd4a470cb293ad5e96bd94689fa2d12d1024eac548479c2e64f967d5f00
size 9001754272

3
mrm8488_Qwen3-14B-ft-limo-Q4_K_S.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:988bf52b121d5158a834773b3bb547ed2801cff08784a9201a7385f98fa2c8dc
size 8573476512

3
mrm8488_Qwen3-14B-ft-limo-Q5_K_L.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:76d648fdce87abec81f3ff1d54a21078367b15b1860d63cc4ca05d553751b7ea
size 10994688672

3
mrm8488_Qwen3-14B-ft-limo-Q5_K_M.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:33d690e326daab01576ae921210ccc8651f87b476acc88caf01183161adb40d5
size 10514570912

3
mrm8488_Qwen3-14B-ft-limo-Q5_K_S.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:a865054dc6f11bf7a1442f03eb7004f91b2aeef6abfa641418500c8854a66d7d
size 10263895712

3
mrm8488_Qwen3-14B-ft-limo-Q6_K.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:8df4f633dc566d70fc7c43ab3fd5959b09ef162107bb507a971817c884de2464
size 12121938592

3
mrm8488_Qwen3-14B-ft-limo-Q6_K_L.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:867e14ca4708b54a7106ef4755976f5a38799a86ddfba1681361d63b043d0090
size 12498739872

3
mrm8488_Qwen3-14B-ft-limo-Q8_0.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:f698c797cbcf4978f7d3d93a2584b6885916869a12a894bf4c8f2b2b94aa8e53
size 15698535072

3
mrm8488_Qwen3-14B-ft-limo-bf16.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:83d76b3b533d78ae5f209ce608b156a079996386651ebf1195a87c98c0099b85
size 29543424384

3
mrm8488_Qwen3-14B-ft-limo.imatrix Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:f4e758e82af9cf03504bbe28ee14afbd0f5133b26372282680dceeac4a5750f1
size 7709778