base_model: LTS-VVE/Teuta
datasets:
- LTS-VVE/Teuta-sq
- LTS-VVE/grammar_sq_0.1
- LTS-VVE/linguistic_sq
- LTS-VVE/Math-physics-dataset-sq
- LTS-VVE/albanian-synthetic
- noxneural/lilium_albanicum_eng_alb
- MIND-Lab/Safety-Evaluation
- shb777/simple-math-steps-7M
- RishiKompelli/TherapyDataset
- microsoft/orca-math-word-problems-200k
- Vezora/Tested-143k-Python-Alpaca
- AI4Chem/ChemPref-DPO-for-Chemistry-data-en
- jkhedri/psychology-dataset
- samhog/psychology-10k
- Amod/mental_health_counseling_conversations
- sayhan/strix-philosophy-qa
- Maverfrick/Rust_dataset
- Neloy262/rust_instruction_dataset
- Tesslate/Rust_Dataset
language:
- en
- sq
library_name: transformers
license: apache-2.0
mradermacher:
readme_rev: 1
quantized_by: mradermacher
tags:
- al
- math
- philosophy
- chemistry
- code
- biology
- climate
- not-for-all-audiences
About
static quants of https://huggingface.co/LTS-VVE/Teuta
For a convenient overview and download list, visit our model page for this model.
weighted/imatrix quants are available at https://huggingface.co/mradermacher/Teuta-i1-GGUF
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.
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 | 1.5 | |
| GGUF | Q3_K_S | 1.6 | |
| GGUF | Q3_K_M | 1.8 | lower quality |
| GGUF | Q3_K_L | 1.9 | |
| GGUF | IQ4_XS | 1.9 | |
| GGUF | Q4_K_S | 2.0 | fast, recommended |
| GGUF | Q4_K_M | 2.1 | fast, recommended |
| GGUF | Q5_K_S | 2.4 | |
| GGUF | Q5_K_M | 2.4 | |
| GGUF | Q6_K | 2.7 | very good quality |
| GGUF | Q8_0 | 3.5 | fast, best quality |
| GGUF | f16 | 6.5 | 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.