bartowski/bralynn_pydevmini1-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/bralynn_pydevmini1-GGUF
Source: Original Platform
This commit is contained in:
ModelHub XC
2026-07-19 22:12:05 +08:00
commit 00b004a79b
28 changed files with 313 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

73
.gitattributes vendored Normal file
View File

@@ -0,0 +1,73 @@
*.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
*.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
bralynn_pydevmini1-IQ3_M.gguf filter=lfs diff=lfs merge=lfs -text
bralynn_pydevmini1-IQ3_XXS.gguf filter=lfs diff=lfs merge=lfs -text
bralynn_pydevmini1-Q2_K_L.gguf filter=lfs diff=lfs merge=lfs -text
bralynn_pydevmini1-Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
bralynn_pydevmini1-Q3_K_S.gguf filter=lfs diff=lfs merge=lfs -text
bralynn_pydevmini1-Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
bralynn_pydevmini1-Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
bralynn_pydevmini1-Q4_K_L.gguf filter=lfs diff=lfs merge=lfs -text
bralynn_pydevmini1-IQ2_M.gguf filter=lfs diff=lfs merge=lfs -text
bralynn_pydevmini1-imatrix.gguf filter=lfs diff=lfs merge=lfs -text
bralynn_pydevmini1-Q5_K_L.gguf filter=lfs diff=lfs merge=lfs -text
bralynn_pydevmini1-IQ4_NL.gguf filter=lfs diff=lfs merge=lfs -text
bralynn_pydevmini1-IQ3_XS.gguf filter=lfs diff=lfs merge=lfs -text
bralynn_pydevmini1-Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
bralynn_pydevmini1-Q5_K_S.gguf filter=lfs diff=lfs merge=lfs -text
bralynn_pydevmini1-IQ4_XS.gguf filter=lfs diff=lfs merge=lfs -text
bralynn_pydevmini1-Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
bralynn_pydevmini1-bf16.gguf filter=lfs diff=lfs merge=lfs -text
bralynn_pydevmini1-Q4_1.gguf filter=lfs diff=lfs merge=lfs -text
bralynn_pydevmini1-Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text
bralynn_pydevmini1-Q4_0.gguf filter=lfs diff=lfs merge=lfs -text
bralynn_pydevmini1-Q3_K_XL.gguf filter=lfs diff=lfs merge=lfs -text
bralynn_pydevmini1-Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
bralynn_pydevmini1-Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text
bralynn_pydevmini1-Q6_K_L.gguf filter=lfs diff=lfs merge=lfs -text

164
README.md Normal file
View File

@@ -0,0 +1,164 @@
---
quantized_by: bartowski
pipeline_tag: text-generation
base_model: bralynn/pydevmini1
base_model_relation: quantized
---
## Llamacpp imatrix Quantizations of pydevmini1 by bralynn
Using <a href="https://github.com/ggml-org/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggml-org/llama.cpp/releases/tag/b6317">b6317</a> for quantization.
Original model: https://huggingface.co/bralynn/pydevmini1
All quants made using imatrix option with dataset from [here](https://gist.github.com/bartowski1182/eb213dccb3571f863da82e99418f81e8) combined with a subset of combined_all_small.parquet from Ed Addario [here](https://huggingface.co/datasets/eaddario/imatrix-calibration/blob/main/combined_all_small.parquet)
Run them in [LM Studio](https://lmstudio.ai/)
Run them directly with [llama.cpp](https://github.com/ggml-org/llama.cpp), or any other llama.cpp based project
## Prompt format
No prompt format found, check original model page
## Download a file (not the whole branch) from below:
| Filename | Quant type | File Size | Split | Description |
| -------- | ---------- | --------- | ----- | ----------- |
| [pydevmini1-bf16.gguf](https://huggingface.co/bartowski/bralynn_pydevmini1-GGUF/blob/main/bralynn_pydevmini1-bf16.gguf) | bf16 | 8.05GB | false | Full BF16 weights. |
| [pydevmini1-Q8_0.gguf](https://huggingface.co/bartowski/bralynn_pydevmini1-GGUF/blob/main/bralynn_pydevmini1-Q8_0.gguf) | Q8_0 | 4.28GB | false | Extremely high quality, generally unneeded but max available quant. |
| [pydevmini1-Q6_K_L.gguf](https://huggingface.co/bartowski/bralynn_pydevmini1-GGUF/blob/main/bralynn_pydevmini1-Q6_K_L.gguf) | Q6_K_L | 3.40GB | false | Uses Q8_0 for embed and output weights. Very high quality, near perfect, *recommended*. |
| [pydevmini1-Q6_K.gguf](https://huggingface.co/bartowski/bralynn_pydevmini1-GGUF/blob/main/bralynn_pydevmini1-Q6_K.gguf) | Q6_K | 3.31GB | false | Very high quality, near perfect, *recommended*. |
| [pydevmini1-Q5_K_L.gguf](https://huggingface.co/bartowski/bralynn_pydevmini1-GGUF/blob/main/bralynn_pydevmini1-Q5_K_L.gguf) | Q5_K_L | 2.98GB | false | Uses Q8_0 for embed and output weights. High quality, *recommended*. |
| [pydevmini1-Q5_K_M.gguf](https://huggingface.co/bartowski/bralynn_pydevmini1-GGUF/blob/main/bralynn_pydevmini1-Q5_K_M.gguf) | Q5_K_M | 2.89GB | false | High quality, *recommended*. |
| [pydevmini1-Q5_K_S.gguf](https://huggingface.co/bartowski/bralynn_pydevmini1-GGUF/blob/main/bralynn_pydevmini1-Q5_K_S.gguf) | Q5_K_S | 2.82GB | false | High quality, *recommended*. |
| [pydevmini1-Q4_1.gguf](https://huggingface.co/bartowski/bralynn_pydevmini1-GGUF/blob/main/bralynn_pydevmini1-Q4_1.gguf) | Q4_1 | 2.60GB | false | Legacy format, similar performance to Q4_K_S but with improved tokens/watt on Apple silicon. |
| [pydevmini1-Q4_K_L.gguf](https://huggingface.co/bartowski/bralynn_pydevmini1-GGUF/blob/main/bralynn_pydevmini1-Q4_K_L.gguf) | Q4_K_L | 2.59GB | false | Uses Q8_0 for embed and output weights. Good quality, *recommended*. |
| [pydevmini1-Q4_K_M.gguf](https://huggingface.co/bartowski/bralynn_pydevmini1-GGUF/blob/main/bralynn_pydevmini1-Q4_K_M.gguf) | Q4_K_M | 2.50GB | false | Good quality, default size for most use cases, *recommended*. |
| [pydevmini1-Q4_K_S.gguf](https://huggingface.co/bartowski/bralynn_pydevmini1-GGUF/blob/main/bralynn_pydevmini1-Q4_K_S.gguf) | Q4_K_S | 2.38GB | false | Slightly lower quality with more space savings, *recommended*. |
| [pydevmini1-Q4_0.gguf](https://huggingface.co/bartowski/bralynn_pydevmini1-GGUF/blob/main/bralynn_pydevmini1-Q4_0.gguf) | Q4_0 | 2.38GB | false | Legacy format, offers online repacking for ARM and AVX CPU inference. |
| [pydevmini1-IQ4_NL.gguf](https://huggingface.co/bartowski/bralynn_pydevmini1-GGUF/blob/main/bralynn_pydevmini1-IQ4_NL.gguf) | IQ4_NL | 2.38GB | false | Similar to IQ4_XS, but slightly larger. Offers online repacking for ARM CPU inference. |
| [pydevmini1-Q3_K_XL.gguf](https://huggingface.co/bartowski/bralynn_pydevmini1-GGUF/blob/main/bralynn_pydevmini1-Q3_K_XL.gguf) | Q3_K_XL | 2.33GB | false | Uses Q8_0 for embed and output weights. Lower quality but usable, good for low RAM availability. |
| [pydevmini1-IQ4_XS.gguf](https://huggingface.co/bartowski/bralynn_pydevmini1-GGUF/blob/main/bralynn_pydevmini1-IQ4_XS.gguf) | IQ4_XS | 2.27GB | false | Decent quality, smaller than Q4_K_S with similar performance, *recommended*. |
| [pydevmini1-Q3_K_L.gguf](https://huggingface.co/bartowski/bralynn_pydevmini1-GGUF/blob/main/bralynn_pydevmini1-Q3_K_L.gguf) | Q3_K_L | 2.24GB | false | Lower quality but usable, good for low RAM availability. |
| [pydevmini1-Q3_K_M.gguf](https://huggingface.co/bartowski/bralynn_pydevmini1-GGUF/blob/main/bralynn_pydevmini1-Q3_K_M.gguf) | Q3_K_M | 2.08GB | false | Low quality. |
| [pydevmini1-IQ3_M.gguf](https://huggingface.co/bartowski/bralynn_pydevmini1-GGUF/blob/main/bralynn_pydevmini1-IQ3_M.gguf) | IQ3_M | 1.96GB | false | Medium-low quality, new method with decent performance comparable to Q3_K_M. |
| [pydevmini1-Q3_K_S.gguf](https://huggingface.co/bartowski/bralynn_pydevmini1-GGUF/blob/main/bralynn_pydevmini1-Q3_K_S.gguf) | Q3_K_S | 1.89GB | false | Low quality, not recommended. |
| [pydevmini1-IQ3_XS.gguf](https://huggingface.co/bartowski/bralynn_pydevmini1-GGUF/blob/main/bralynn_pydevmini1-IQ3_XS.gguf) | IQ3_XS | 1.81GB | false | Lower quality, new method with decent performance, slightly better than Q3_K_S. |
| [pydevmini1-Q2_K_L.gguf](https://huggingface.co/bartowski/bralynn_pydevmini1-GGUF/blob/main/bralynn_pydevmini1-Q2_K_L.gguf) | Q2_K_L | 1.76GB | false | Uses Q8_0 for embed and output weights. Very low quality but surprisingly usable. |
| [pydevmini1-IQ3_XXS.gguf](https://huggingface.co/bartowski/bralynn_pydevmini1-GGUF/blob/main/bralynn_pydevmini1-IQ3_XXS.gguf) | IQ3_XXS | 1.67GB | false | Lower quality, new method with decent performance, comparable to Q3 quants. |
| [pydevmini1-Q2_K.gguf](https://huggingface.co/bartowski/bralynn_pydevmini1-GGUF/blob/main/bralynn_pydevmini1-Q2_K.gguf) | Q2_K | 1.67GB | false | Very low quality but surprisingly usable. |
| [pydevmini1-IQ2_M.gguf](https://huggingface.co/bartowski/bralynn_pydevmini1-GGUF/blob/main/bralynn_pydevmini1-IQ2_M.gguf) | IQ2_M | 1.51GB | 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/bralynn_pydevmini1-GGUF --include "bralynn_pydevmini1-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/bralynn_pydevmini1-GGUF --include "bralynn_pydevmini1-Q8_0/*" --local-dir ./
```
You can either specify a new local-dir (bralynn_pydevmini1-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/ggml-org/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/ggml-org/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/ggml-org/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/ggml-org/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

3
bralynn_pydevmini1-IQ2_M.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:35d16101db7712a597a8e5956284a75ca17c0542f10e6db3044ca2b7eb773f13
size 1512984768

3
bralynn_pydevmini1-IQ3_M.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:bbc7937f014261772a7c744ef2452fc7180f771927cc616ba886310670b21fe8
size 1962897088

3
bralynn_pydevmini1-IQ3_XS.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:3894b5221b0638e35bc653c1eb9cd586c3b82085c8ab519833e990da1049efc8
size 1814376128

3
bralynn_pydevmini1-IQ3_XXS.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:1a98a9c1b1b05094e355ad7d0662e1a88249e54d1b9c14a1e48d087dc95fec6a
size 1670189248

3
bralynn_pydevmini1-IQ4_NL.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:1cbf0cb859301e9414a4e463171bd21562d0b7b1096479e67bad312c227fd2be
size 2381344448

3
bralynn_pydevmini1-IQ4_XS.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:24a5928424ba79b817fd314d23ab9c0bfb9c8d8a8e55277ad62337fc736cf941
size 2270752448

3
bralynn_pydevmini1-Q2_K.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:679e27264e37f39ab9c5fa58a558c8ed31f438ebdd548bd593dd425e7484e8f3
size 1669500608

3
bralynn_pydevmini1-Q2_K_L.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:c57f8d310cb9eecf59005c40ba0511298f2b202e6fb8cdf323548a4a448ff1b8
size 1763700928

3
bralynn_pydevmini1-Q3_K_L.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:58ac37069dcdf5236616dd80452590a65efa3d47f8a4f11cb45448bd07ed132d
size 2239786688

3
bralynn_pydevmini1-Q3_K_M.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:a4c09ac67545f4eb867d0a576bc80808ca403b9bb3b1728e6739683c8fa03562
size 2075619008

3
bralynn_pydevmini1-Q3_K_S.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:dc158556f3d117e9d1245cd1ee23a55c323d5a54d9b987a927732309851cdb00
size 1886998208

3
bralynn_pydevmini1-Q3_K_XL.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:29c71d108532c0c69d2ebc18f5ebd71b40b5c49c334242b17093fb9656e6bead
size 2333987008

3
bralynn_pydevmini1-Q4_0.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:08d79c9e394533c4f3ab9cb262a7e603239620e137a94aa281eb4846c25fdb2f
size 2375773888

3
bralynn_pydevmini1-Q4_1.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:88d87f8135e661d0983dc2ea5f4f9ba0740787a5573cefbc2284c881759e176b
size 2596630208

3
bralynn_pydevmini1-Q4_K_L.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:6e40bafda678cee3842fd9b8798d444e1811672211b23324ad243f10070f1b75
size 2591482048

3
bralynn_pydevmini1-Q4_K_M.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:1d2f5c585befde0878415d1a0ca601b3899622569a3c7580afafe7c404c9b959
size 2497281728

3
bralynn_pydevmini1-Q4_K_S.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:523e0c9fd19815384cbd899ed2640232a6e5eb9c97b5270de22356c218275cc7
size 2383310528

3
bralynn_pydevmini1-Q5_K_L.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:02ba454618e78e18431a2a9a3cdd09083cc0a5204f751733656046b36977cf8c
size 2983715008

3
bralynn_pydevmini1-Q5_K_M.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:3978ed1112083eddd4199145eee8ebff0402ca4b53be283feedd6f62cd28176e
size 2889514688

3
bralynn_pydevmini1-Q5_K_S.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:d9d37077021ed3a9977edbe4e7227ddb9f96e3dc647f5c455b5d87c244af5bd4
size 2823712448

3
bralynn_pydevmini1-Q6_K.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:304797e34139677ec1eca8d0b8ab4765398ed21c7844942405576254a80329d4
size 3306262208

3
bralynn_pydevmini1-Q6_K_L.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:64edd3bfc3c328399dbb14425f07f005b77529226dd7bbcab1872c4f6b4ebb5f
size 3400462528

3
bralynn_pydevmini1-Q8_0.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:b9486bbfeb635d0d23f2e621d4cca33151dbf19997f1ffce43e46bec8f6588dc
size 4280406208

3
bralynn_pydevmini1-bf16.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:94570d9f76f014d09c3f0bc5c88a731738d02cb60af667a7f44bfba67b23cf9a
size 8051285920

3
bralynn_pydevmini1-imatrix.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:e33d6c3d95374e70202069e9aec4361e757a7e4a8b0424fdcd16c865f955a48d
size 3872640

1
configuration.json Normal file
View File

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