--- base_model: - mahiatlinux/merged1and2-and-dolphin - automerger/YamShadow-7B exported_from: mahiatlinux/ShadowDolph-7B-v1 language: - en library_name: transformers license: apache-2.0 quantized_by: mradermacher tags: - merge - mergekit - lazymergekit - mahiatlinux/merged1and2-and-dolphin - automerger/YamShadow-7B --- ## About static quants of https://huggingface.co/mahiatlinux/ShadowDolph-7B-v1 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](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/ShadowDolph-7B-v1-GGUF/resolve/main/ShadowDolph-7B-v1.Q4_K_S.gguf) | Q4_K_S | 4.4 | fast, recommended | 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 ## 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.