Downloads · 30 days
151
37% of all-time downloads
mradermacher/Merged-RP-Stew-V2-51B-GGUF
Merged-RP-Stew-V2-51B-GGUF is a machine learning model from mradermacher. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as other.
static quants of https://huggingface.co/Kotokin/Merged-RP-Stew-V2-51B
Downloads · 30 days
151
37% of all-time downloads
All-time downloads
412
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414 GB
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.gguf360 GB · 87%
From the Hugging Face model README
static quants of https://huggingface.co/Kotokin/Merged-RP-Stew-V2-51B
<!-- provided-files -->weighted/imatrix quants are available at https://huggingface.co/mradermacher/Merged-RP-Stew-V2-51B-i1-GGUF
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.
(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 | 19.1 | |
| GGUF | IQ3_XS | 21.2 | |
| GGUF | Q3_K_S | 22.3 | |
| GGUF | IQ3_S | 22.3 | beats Q3_K* |
| GGUF | IQ3_M | 23.2 | |
| GGUF | Q3_K_M | 24.8 | lower quality |
| GGUF | Q3_K_L | 27.0 | |
| GGUF | IQ4_XS | 27.8 | |
| GGUF | Q4_K_S | 29.2 | fast, recommended |
| GGUF | Q4_K_M | 30.8 | fast, recommended |
| GGUF | Q5_K_S | 35.3 | |
| GGUF | Q5_K_M | 36.2 | |
| GGUF | Q6_K | 42.0 | very good quality |
| PART 1 PART 2 | Q8_0 | 54.4 | fast, best quality |
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
See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized.
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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