---
base_model: ellamind/propella-1-0.6b
language:
- eng
- spa
- ita
- fra
- deu
- pol
- ukr
- nld
- tha
- jpn
- heb
- ell
- kor
- isl
- dan
- cat
- slk
- rus
- kat
- por
- ben
- fas
- ekk
- fin
- tur
- swe
- ind
- ces
- lit
- slv
- vie
- eus
- bul
- mlt
- lvs
- nob
- hun
- urd
- ron
- glg
- gle
- nno
- ltg
- yue
- cmn
- hrv
- arb
- bos
- mkd
- srp
- hin
- als
- sqi
- est
- nor
- lav
- swa
library_name: transformers
license: apache-2.0
mradermacher:
  readme_rev: 1
quantized_by: mradermacher
---
## About

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<!-- ### quants:  x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
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static quants of https://huggingface.co/ellamind/propella-1-0.6b

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***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#propella-1-0.6b-GGUF).***

weighted/imatrix quants are available at https://huggingface.co/mradermacher/propella-1-0.6b-i1-GGUF
## Usage

If you are unsure how to use GGUF files, refer to one of [TheBloke's
READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) 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](https://huggingface.co/mradermacher/propella-1-0.6b-GGUF/resolve/main/propella-1-0.6b.Q2_K.gguf) | Q2_K | 0.4 |  |
| [GGUF](https://huggingface.co/mradermacher/propella-1-0.6b-GGUF/resolve/main/propella-1-0.6b.Q3_K_S.gguf) | Q3_K_S | 0.5 |  |
| [GGUF](https://huggingface.co/mradermacher/propella-1-0.6b-GGUF/resolve/main/propella-1-0.6b.Q3_K_M.gguf) | Q3_K_M | 0.5 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/propella-1-0.6b-GGUF/resolve/main/propella-1-0.6b.Q3_K_L.gguf) | Q3_K_L | 0.5 |  |
| [GGUF](https://huggingface.co/mradermacher/propella-1-0.6b-GGUF/resolve/main/propella-1-0.6b.IQ4_XS.gguf) | IQ4_XS | 0.6 |  |
| [GGUF](https://huggingface.co/mradermacher/propella-1-0.6b-GGUF/resolve/main/propella-1-0.6b.Q4_K_S.gguf) | Q4_K_S | 0.6 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/propella-1-0.6b-GGUF/resolve/main/propella-1-0.6b.Q4_K_M.gguf) | Q4_K_M | 0.6 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/propella-1-0.6b-GGUF/resolve/main/propella-1-0.6b.Q5_K_S.gguf) | Q5_K_S | 0.6 |  |
| [GGUF](https://huggingface.co/mradermacher/propella-1-0.6b-GGUF/resolve/main/propella-1-0.6b.Q5_K_M.gguf) | Q5_K_M | 0.7 |  |
| [GGUF](https://huggingface.co/mradermacher/propella-1-0.6b-GGUF/resolve/main/propella-1-0.6b.Q6_K.gguf) | Q6_K | 0.7 | very good quality |
| [GGUF](https://huggingface.co/mradermacher/propella-1-0.6b-GGUF/resolve/main/propella-1-0.6b.Q8_0.gguf) | Q8_0 | 0.9 | fast, best quality |
| [GGUF](https://huggingface.co/mradermacher/propella-1-0.6b-GGUF/resolve/main/propella-1-0.6b.f16.gguf) | f16 | 1.6 | 16 bpw, overkill |

Here is a handy graph by ikawrakow comparing some lower-quality quant
types (lower is better):

![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)

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](https://www.nethype.de/), for letting
me use its servers and providing upgrades to my workstation to enable
this work in my free time.

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