đ Llama-3.1-8B-Instuct-Uz Quantized Model
This project provides static quantizations of the Llama-3.1-8B-Instuct-Uz model, offering various quantization types for different usage scenarios.
⨠Features
- Multi-language Support: Supports both Uzbek (
uz) and English (en).
- Diverse Datasets: Trained on multiple datasets including
yahma/alpaca-cleaned, behbudiy/alpaca-cleaned-uz, and behbudiy/translation-instruction.
- Multiple Quantization Types: Offers a range of quantization types with different sizes and qualities.
đĻ Model Information
| Property |
Details |
| Base Model |
behbudiy/Llama-3.1-8B-Instuct-Uz |
| Datasets |
yahma/alpaca-cleaned, behbudiy/alpaca-cleaned-uz, behbudiy/translation-instruction |
| Languages |
uz, en |
| Library Name |
transformers |
| License |
llama3.1 |
| Quantized By |
mradermacher |
| Tags |
llama, text-generation-inference, summarization, translation, question-answering |
đ Quick Start
About
These are static quants of https://huggingface.co/behbudiy/Llama-3.1-8B-Instuct-Uz.
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.
Usage
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.
đ Documentation
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 |
3.3 |
|
| GGUF |
IQ3_XS |
3.6 |
|
| GGUF |
Q3_K_S |
3.8 |
|
| GGUF |
IQ3_S |
3.8 |
beats Q3_K* |
| GGUF |
IQ3_M |
3.9 |
|
| GGUF |
Q3_K_M |
4.1 |
lower quality |
| GGUF |
Q3_K_L |
4.4 |
|
| GGUF |
IQ4_XS |
4.6 |
|
| GGUF |
Q4_K_S |
4.8 |
fast, recommended |
| GGUF |
Q4_K_M |
5.0 |
fast, recommended |
| GGUF |
Q5_K_S |
5.7 |
|
| GGUF |
Q5_K_M |
5.8 |
|
| GGUF |
Q6_K |
6.7 |
very good quality |
| GGUF |
Q8_0 |
8.6 |
fast, best quality |
| GGUF |
f16 |
16.2 |
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.
đ 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.
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Transformers