đ Lacia_sum_small_v1 Quantized Model
This project provides static quantizations of the Lacia_sum_small_v1 model, offering various quantization types for different needs in natural language processing.
đ Quick Start
If you are unsure how to use GGUF files, refer to one of TheBloke's READMEs for more details, including on how to concatenate multi - part files.
⨠Features
- Multilingual Support: Supports both Russian (
ru
) and English (en
).
- Multiple Quantization Types: Offers a variety of quantization types for different performance and quality trade - offs.
- Transformer - Based: Built on the Transformer architecture, suitable for tasks like summarization and natural language processing.
đĻ Installation
No specific installation steps are provided in the original document.
đ Documentation
About
Static quants of https://huggingface.co/2KKLabs/Lacia_sum_small_v1.
Weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
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 |
Q2_K |
0.2 |
|
GGUF |
Q3_K_S |
0.2 |
|
GGUF |
Q3_K_M |
0.2 |
lower quality |
GGUF |
Q3_K_L |
0.2 |
|
GGUF |
IQ4_XS |
0.2 |
|
GGUF |
Q4_K_S |
0.2 |
fast, recommended |
GGUF |
Q4_K_M |
0.2 |
fast, recommended |
GGUF |
Q5_K_S |
0.3 |
|
GGUF |
Q5_K_M |
0.3 |
|
GGUF |
Q6_K |
0.3 |
very good quality |
GGUF |
Q8_0 |
0.3 |
fast, best quality |
GGUF |
f16 |
0.5 |
16 bpw, overkill |
Here is a handy graph by ikawrakow comparing some lower - quality quant types (lower is better):

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, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time.
đ License
This project is licensed under the cc - by - nc - 4.0
license.
đ Model Information
Property |
Details |
Base Model |
2KKLabs/Lacia_sum_small_v1 |
Language |
ru, en |
Library Name |
transformers |
Quantized By |
mradermacher |
Tags |
summarization, natural - language - processing, text - summarization, machine - learning, deep - learning, transformer, artificial - intelligence, text - analysis, sequence - to - sequence, pytorch, tensorflow, safetensors, t5 |