--- base_model: - Kukedlc/SomeModelsMerge-7b - Kukedlc/MyModelsMerge-7b exported_from: Kukedlc/NeuralGanesha-7b language: - en library_name: transformers license: apache-2.0 quantized_by: mradermacher tags: - merge - mergekit - lazymergekit - Kukedlc/SomeModelsMerge-7b - Kukedlc/MyModelsMerge-7b --- ## About static quants of https://huggingface.co/Kukedlc/NeuralGanesha-7b 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/NeuralGanesha-7b-GGUF/resolve/main/NeuralGanesha-7b.Q2_K.gguf) | Q2_K | 3.0 | | | [GGUF](https://huggingface.co/mradermacher/NeuralGanesha-7b-GGUF/resolve/main/NeuralGanesha-7b.Q3_K_S.gguf) | Q3_K_S | 3.4 | | | [GGUF](https://huggingface.co/mradermacher/NeuralGanesha-7b-GGUF/resolve/main/NeuralGanesha-7b.IQ3_S.gguf) | IQ3_S | 3.4 | beats Q3_K* | | [GGUF](https://huggingface.co/mradermacher/NeuralGanesha-7b-GGUF/resolve/main/NeuralGanesha-7b.Q3_K_M.gguf) | Q3_K_M | 3.8 | lower quality | | [GGUF](https://huggingface.co/mradermacher/NeuralGanesha-7b-GGUF/resolve/main/NeuralGanesha-7b.Q3_K_L.gguf) | Q3_K_L | 4.1 | | | [GGUF](https://huggingface.co/mradermacher/NeuralGanesha-7b-GGUF/resolve/main/NeuralGanesha-7b.Q4_0.gguf) | Q4_0 | 4.4 | | | [GGUF](https://huggingface.co/mradermacher/NeuralGanesha-7b-GGUF/resolve/main/NeuralGanesha-7b.Q4_K_S.gguf) | Q4_K_S | 4.4 | fast, recommended | | [GGUF](https://huggingface.co/mradermacher/NeuralGanesha-7b-GGUF/resolve/main/NeuralGanesha-7b.Q4_K_M.gguf) | Q4_K_M | 4.6 | fast, recommended | | [GGUF](https://huggingface.co/mradermacher/NeuralGanesha-7b-GGUF/resolve/main/NeuralGanesha-7b.Q6_K.gguf) | Q6_K | 6.2 | very good quality | | [GGUF](https://huggingface.co/mradermacher/NeuralGanesha-7b-GGUF/resolve/main/NeuralGanesha-7b.Q8_0.gguf) | Q8_0 | 7.9 | fast, best quality | 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.