base_model: euclaise/Memphis-scribe-3B
datasets:
- euclaise/TinyCoT
- euclaise/mathoverflow-accepted
- euclaise/reddit-instruct-curated
- euclaise/WritingPrompts_curated
- sablo/oasst2_curated
- euclaise/mathqa_programs
- BEE-spoke-data/coedit-reworded-deduped
- pszemraj/booksum-short
- euclaise/reddit-instruct
- euclaise/SciCoT
- euirim/goodwiki
- neulab/conala
- squad
- ropes
- euclaise/logician
- chargoddard/rpguild
- lemonilia/LimaRP
language:
- en
library_name: transformers
license: cc-by-4.0
quantized_by: mradermacher
tags:
- supertrainer2000
- not-for-all-audiences
- writing
- roleplay
About
static quants of https://huggingface.co/euclaise/Memphis-scribe-3B
weighted/imatrix quants are available at https://huggingface.co/mradermacher/Memphis-scribe-3B-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 | 1.2 | |
| GGUF | Q3_K_S | 1.4 | |
| GGUF | Q3_K_M | 1.5 | lower quality |
| GGUF | Q3_K_L | 1.6 | |
| GGUF | IQ4_XS | 1.6 | |
| GGUF | Q4_K_S | 1.7 | fast, recommended |
| GGUF | Q4_K_M | 1.8 | fast, recommended |
| GGUF | Q5_K_S | 2.0 | |
| GGUF | Q5_K_M | 2.1 | |
| GGUF | Q6_K | 2.4 | very good quality |
| GGUF | Q8_0 | 3.1 | 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
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.