--- language: - en library_name: transformers license: cc-by-nc-4.0 quantized_by: mradermacher --- ## About static quants of https://huggingface.co./Sao10K/Fimbulvetr-11B-v2 weighted/imatrix quants are available at https://huggingface.co./mradermacher/Fimbulvetr-11B-v2-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/Fimbulvetr-11B-v2-GGUF/resolve/main/Fimbulvetr-11B-v2.Q2_K.gguf) | Q2_K | 4.3 | | | [GGUF](https://huggingface.co./mradermacher/Fimbulvetr-11B-v2-GGUF/resolve/main/Fimbulvetr-11B-v2.IQ3_XS.gguf) | IQ3_XS | 4.7 | | | [GGUF](https://huggingface.co./mradermacher/Fimbulvetr-11B-v2-GGUF/resolve/main/Fimbulvetr-11B-v2.Q3_K_S.gguf) | Q3_K_S | 4.9 | | | [GGUF](https://huggingface.co./mradermacher/Fimbulvetr-11B-v2-GGUF/resolve/main/Fimbulvetr-11B-v2.IQ3_S.gguf) | IQ3_S | 4.9 | fast, beats Q3_K* | | [GGUF](https://huggingface.co./mradermacher/Fimbulvetr-11B-v2-GGUF/resolve/main/Fimbulvetr-11B-v2.IQ3_M.gguf) | IQ3_M | 5.1 | | | [GGUF](https://huggingface.co./mradermacher/Fimbulvetr-11B-v2-GGUF/resolve/main/Fimbulvetr-11B-v2.Q3_K_M.gguf) | Q3_K_M | 5.5 | lower quality | | [GGUF](https://huggingface.co./mradermacher/Fimbulvetr-11B-v2-GGUF/resolve/main/Fimbulvetr-11B-v2.Q3_K_L.gguf) | Q3_K_L | 5.9 | | | [GGUF](https://huggingface.co./mradermacher/Fimbulvetr-11B-v2-GGUF/resolve/main/Fimbulvetr-11B-v2.IQ4_XS.gguf) | IQ4_XS | 6.1 | | | [GGUF](https://huggingface.co./mradermacher/Fimbulvetr-11B-v2-GGUF/resolve/main/Fimbulvetr-11B-v2.Q4_K_S.gguf) | Q4_K_S | 6.4 | fast, medium quality | | [GGUF](https://huggingface.co./mradermacher/Fimbulvetr-11B-v2-GGUF/resolve/main/Fimbulvetr-11B-v2.Q4_K_M.gguf) | Q4_K_M | 6.7 | fast, medium quality | | [GGUF](https://huggingface.co./mradermacher/Fimbulvetr-11B-v2-GGUF/resolve/main/Fimbulvetr-11B-v2.Q5_K_S.gguf) | Q5_K_S | 7.7 | | | [GGUF](https://huggingface.co./mradermacher/Fimbulvetr-11B-v2-GGUF/resolve/main/Fimbulvetr-11B-v2.Q5_K_M.gguf) | Q5_K_M | 7.9 | | | [GGUF](https://huggingface.co./mradermacher/Fimbulvetr-11B-v2-GGUF/resolve/main/Fimbulvetr-11B-v2.Q6_K.gguf) | Q6_K | 9.1 | very good quality | | [GGUF](https://huggingface.co./mradermacher/Fimbulvetr-11B-v2-GGUF/resolve/main/Fimbulvetr-11B-v2.Q8_0.gguf) | Q8_0 | 11.6 | 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.