bartowski/soob3123_amoral-gemma3-4B-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/soob3123_amoral-gemma3-4B-GGUF
Source: Original Platform
This commit is contained in:
ModelHub XC
2026-07-18 08:55:06 +08:00
commit 0e576ae5a5
28 changed files with 302 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
*.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

182
README.md Normal file
View File

@@ -0,0 +1,182 @@
---
quantized_by: bartowski
pipeline_tag: text-generation
license: apache-2.0
base_model_relation: quantized
language:
- en
base_model: soob3123/amoral-gemma3-4B
tags:
- text-generation-inference
- transformers
- gemma3
- analytical-tasks
- bias-neutralization
- uncensored
---
## Llamacpp imatrix Quantizations of amoral-gemma3-4B by soob3123
Using <a href="https://github.com/ggerganov/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggerganov/llama.cpp/releases/tag/b4925">b4925</a> for quantization.
Original model: https://huggingface.co/soob3123/amoral-gemma3-4B
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
```
<bos><start_of_turn>user
{system_prompt}
{prompt}<end_of_turn>
<start_of_turn>model
<end_of_turn>
<start_of_turn>model
```
## Download a file (not the whole branch) from below:
| Filename | Quant type | File Size | Split | Description |
| -------- | ---------- | --------- | ----- | ----------- |
| [amoral-gemma3-4B-bf16.gguf](https://huggingface.co/bartowski/soob3123_amoral-gemma3-4B-GGUF/blob/main/soob3123_amoral-gemma3-4B-bf16.gguf) | bf16 | 7.77GB | false | Full BF16 weights. |
| [amoral-gemma3-4B-Q8_0.gguf](https://huggingface.co/bartowski/soob3123_amoral-gemma3-4B-GGUF/blob/main/soob3123_amoral-gemma3-4B-Q8_0.gguf) | Q8_0 | 4.13GB | false | Extremely high quality, generally unneeded but max available quant. |
| [amoral-gemma3-4B-Q6_K_L.gguf](https://huggingface.co/bartowski/soob3123_amoral-gemma3-4B-GGUF/blob/main/soob3123_amoral-gemma3-4B-Q6_K_L.gguf) | Q6_K_L | 3.35GB | false | Uses Q8_0 for embed and output weights. Very high quality, near perfect, *recommended*. |
| [amoral-gemma3-4B-Q6_K.gguf](https://huggingface.co/bartowski/soob3123_amoral-gemma3-4B-GGUF/blob/main/soob3123_amoral-gemma3-4B-Q6_K.gguf) | Q6_K | 3.19GB | false | Very high quality, near perfect, *recommended*. |
| [amoral-gemma3-4B-Q5_K_L.gguf](https://huggingface.co/bartowski/soob3123_amoral-gemma3-4B-GGUF/blob/main/soob3123_amoral-gemma3-4B-Q5_K_L.gguf) | Q5_K_L | 2.99GB | false | Uses Q8_0 for embed and output weights. High quality, *recommended*. |
| [amoral-gemma3-4B-Q5_K_M.gguf](https://huggingface.co/bartowski/soob3123_amoral-gemma3-4B-GGUF/blob/main/soob3123_amoral-gemma3-4B-Q5_K_M.gguf) | Q5_K_M | 2.83GB | false | High quality, *recommended*. |
| [amoral-gemma3-4B-Q5_K_S.gguf](https://huggingface.co/bartowski/soob3123_amoral-gemma3-4B-GGUF/blob/main/soob3123_amoral-gemma3-4B-Q5_K_S.gguf) | Q5_K_S | 2.76GB | false | High quality, *recommended*. |
| [amoral-gemma3-4B-Q4_K_L.gguf](https://huggingface.co/bartowski/soob3123_amoral-gemma3-4B-GGUF/blob/main/soob3123_amoral-gemma3-4B-Q4_K_L.gguf) | Q4_K_L | 2.65GB | false | Uses Q8_0 for embed and output weights. Good quality, *recommended*. |
| [amoral-gemma3-4B-Q4_1.gguf](https://huggingface.co/bartowski/soob3123_amoral-gemma3-4B-GGUF/blob/main/soob3123_amoral-gemma3-4B-Q4_1.gguf) | Q4_1 | 2.56GB | false | Legacy format, similar performance to Q4_K_S but with improved tokens/watt on Apple silicon. |
| [amoral-gemma3-4B-Q4_K_M.gguf](https://huggingface.co/bartowski/soob3123_amoral-gemma3-4B-GGUF/blob/main/soob3123_amoral-gemma3-4B-Q4_K_M.gguf) | Q4_K_M | 2.49GB | false | Good quality, default size for most use cases, *recommended*. |
| [amoral-gemma3-4B-Q3_K_XL.gguf](https://huggingface.co/bartowski/soob3123_amoral-gemma3-4B-GGUF/blob/main/soob3123_amoral-gemma3-4B-Q3_K_XL.gguf) | Q3_K_XL | 2.40GB | false | Uses Q8_0 for embed and output weights. Lower quality but usable, good for low RAM availability. |
| [amoral-gemma3-4B-Q4_K_S.gguf](https://huggingface.co/bartowski/soob3123_amoral-gemma3-4B-GGUF/blob/main/soob3123_amoral-gemma3-4B-Q4_K_S.gguf) | Q4_K_S | 2.38GB | false | Slightly lower quality with more space savings, *recommended*. |
| [amoral-gemma3-4B-Q4_0.gguf](https://huggingface.co/bartowski/soob3123_amoral-gemma3-4B-GGUF/blob/main/soob3123_amoral-gemma3-4B-Q4_0.gguf) | Q4_0 | 2.37GB | false | Legacy format, offers online repacking for ARM and AVX CPU inference. |
| [amoral-gemma3-4B-IQ4_NL.gguf](https://huggingface.co/bartowski/soob3123_amoral-gemma3-4B-GGUF/blob/main/soob3123_amoral-gemma3-4B-IQ4_NL.gguf) | IQ4_NL | 2.36GB | false | Similar to IQ4_XS, but slightly larger. Offers online repacking for ARM CPU inference. |
| [amoral-gemma3-4B-IQ4_XS.gguf](https://huggingface.co/bartowski/soob3123_amoral-gemma3-4B-GGUF/blob/main/soob3123_amoral-gemma3-4B-IQ4_XS.gguf) | IQ4_XS | 2.26GB | false | Decent quality, smaller than Q4_K_S with similar performance, *recommended*. |
| [amoral-gemma3-4B-Q3_K_L.gguf](https://huggingface.co/bartowski/soob3123_amoral-gemma3-4B-GGUF/blob/main/soob3123_amoral-gemma3-4B-Q3_K_L.gguf) | Q3_K_L | 2.24GB | false | Lower quality but usable, good for low RAM availability. |
| [amoral-gemma3-4B-Q3_K_M.gguf](https://huggingface.co/bartowski/soob3123_amoral-gemma3-4B-GGUF/blob/main/soob3123_amoral-gemma3-4B-Q3_K_M.gguf) | Q3_K_M | 2.10GB | false | Low quality. |
| [amoral-gemma3-4B-IQ3_M.gguf](https://huggingface.co/bartowski/soob3123_amoral-gemma3-4B-GGUF/blob/main/soob3123_amoral-gemma3-4B-IQ3_M.gguf) | IQ3_M | 1.99GB | false | Medium-low quality, new method with decent performance comparable to Q3_K_M. |
| [amoral-gemma3-4B-Q3_K_S.gguf](https://huggingface.co/bartowski/soob3123_amoral-gemma3-4B-GGUF/blob/main/soob3123_amoral-gemma3-4B-Q3_K_S.gguf) | Q3_K_S | 1.94GB | false | Low quality, not recommended. |
| [amoral-gemma3-4B-Q2_K_L.gguf](https://huggingface.co/bartowski/soob3123_amoral-gemma3-4B-GGUF/blob/main/soob3123_amoral-gemma3-4B-Q2_K_L.gguf) | Q2_K_L | 1.89GB | false | Uses Q8_0 for embed and output weights. Very low quality but surprisingly usable. |
| [amoral-gemma3-4B-IQ3_XS.gguf](https://huggingface.co/bartowski/soob3123_amoral-gemma3-4B-GGUF/blob/main/soob3123_amoral-gemma3-4B-IQ3_XS.gguf) | IQ3_XS | 1.86GB | false | Lower quality, new method with decent performance, slightly better than Q3_K_S. |
| [amoral-gemma3-4B-Q2_K.gguf](https://huggingface.co/bartowski/soob3123_amoral-gemma3-4B-GGUF/blob/main/soob3123_amoral-gemma3-4B-Q2_K.gguf) | Q2_K | 1.73GB | false | Very low quality but surprisingly usable. |
| [amoral-gemma3-4B-IQ3_XXS.gguf](https://huggingface.co/bartowski/soob3123_amoral-gemma3-4B-GGUF/blob/main/soob3123_amoral-gemma3-4B-IQ3_XXS.gguf) | IQ3_XXS | 1.69GB | false | Lower quality, new method with decent performance, comparable to Q3 quants. |
| [amoral-gemma3-4B-IQ2_M.gguf](https://huggingface.co/bartowski/soob3123_amoral-gemma3-4B-GGUF/blob/main/soob3123_amoral-gemma3-4B-IQ2_M.gguf) | IQ2_M | 1.54GB | false | Relatively low quality, uses SOTA techniques to be surprisingly 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/soob3123_amoral-gemma3-4B-GGUF --include "soob3123_amoral-gemma3-4B-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/soob3123_amoral-gemma3-4B-GGUF --include "soob3123_amoral-gemma3-4B-Q8_0/*" --local-dir ./
```
You can either specify a new local-dir (soob3123_amoral-gemma3-4B-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
soob3123_amoral-gemma3-4B-IQ2_M.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:e0da8a86128dd58353bac11e20103d8f90e37603c04cf35748eae150d5948fe8
size 1537982752

3
soob3123_amoral-gemma3-4B-IQ3_M.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:3c67c6cd16904b26cf82e3c7f70b4a887f4d4c6d787bb510da7accbeac763b09
size 1986803232

3
soob3123_amoral-gemma3-4B-IQ3_XS.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:11638896f18098f10ae486eda0389e8cca976845cdbd6d0574ca89db4f574845
size 1863390752

3
soob3123_amoral-gemma3-4B-IQ3_XXS.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:07e55675630f42ccafa7ede1e1fb6e8497f48725094ad8dd06b63486723d114f
size 1689452832

3
soob3123_amoral-gemma3-4B-IQ4_NL.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:40c72c8aae9b1c9cd19420dc386984441e0cde7c01467dd81185d6d9c35cb1dc
size 2363512352

3
soob3123_amoral-gemma3-4B-IQ4_XS.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:7a72183d8c6c8900d1ffe77a33d508bc31d6e3b59e41ca50f94eb2377bdbce11
size 2263242272

3
soob3123_amoral-gemma3-4B-Q2_K.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:82f005250a2e8bac4e3932c226f2c2a576ef76791e95a009c0883093abc782bf
size 1729164832

3
soob3123_amoral-gemma3-4B-Q2_K_L.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:236d560008e3f68d4483f19701a2d012b85f52826e316f2e40ad81e0236ef955
size 1891733792

3
soob3123_amoral-gemma3-4B-Q3_K_L.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:397401739db6278736d8ef6de8915496c45b6f9543c9bf97d5f886e63e840854
size 2236085792

3
soob3123_amoral-gemma3-4B-Q3_K_M.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:2f2e10a754170f89693280937009642d29f53b952ce599cf72bd6d649784b125
size 2098460192

3
soob3123_amoral-gemma3-4B-Q3_K_S.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:5f1ab4a5d27015f6ec1d2630a6150d7845cbc26abf3fa1dd3e5100d9310a60de
size 1937364512

3
soob3123_amoral-gemma3-4B-Q3_K_XL.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:9434a14fc5ca5244769fa73ef232cd5963b10448def1cb9900ff76427b7bf334
size 2398654752

3
soob3123_amoral-gemma3-4B-Q4_0.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:c46cebb6c40002b0edb4de6434696d9b86040e33dd6a5e2c7b2954e5bae396ab
size 2370065952

3
soob3123_amoral-gemma3-4B-Q4_1.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:42920b2b0895742e8f1948b40cc40cc4fefdcd6fed645ebb0bd999a47086077b
size 2564052512

3
soob3123_amoral-gemma3-4B-Q4_K_L.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:f06bcf779c6422af2081d035534eab609381eb4cae544b83fa6e7dc8c8892230
size 2652463392

3
soob3123_amoral-gemma3-4B-Q4_K_M.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:73ecf0492e401c24de93ab74701f4b377cfd7d54981a75aab3fd2065fdda28d1
size 2489894432

3
soob3123_amoral-gemma3-4B-Q4_K_S.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:007aedafbd9827a41e97ee04f62b8a2981f0942856f081875791fb4223677576
size 2377930272

3
soob3123_amoral-gemma3-4B-Q5_K_L.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:2e668295920268b027ed09c93ccd84502b2a2d8fdd632a1867ae794bdd7bd3c3
size 2992267552

3
soob3123_amoral-gemma3-4B-Q5_K_M.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:f73b74491b8768fa18246322a2c26cd9ada42c9e9f830a4cd7dfb632cc608530
size 2829698592

3
soob3123_amoral-gemma3-4B-Q5_K_S.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:9cfa50bed00eddb0eb9800bd30b6e0f0ab1428a5959c7efd7a8881391a28716a
size 2764592672

3
soob3123_amoral-gemma3-4B-Q6_K.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:3654877d50e6500e5ce7d076c64cac6410769154cd47d26f6f754f84c1811368
size 3190740512

3
soob3123_amoral-gemma3-4B-Q6_K_L.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:982cf86b4d5760b2bdb449423e9c7578530d081ca22e2ba98338176cc3143147
size 3353309472

3
soob3123_amoral-gemma3-4B-Q8_0.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:669b85fc18b8c67c9f4d0d5e0f5ea63cead4939bf469d51ac237d5bb3c2241ad
size 4130402592

3
soob3123_amoral-gemma3-4B-bf16.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:2bedb7a1362237646ffd7d76d3f079e2ede212d3f3d087464a0e45550a0849a0
size 7767803904

BIN
soob3123_amoral-gemma3-4B.imatrix Normal file
View File

Binary file not shown.