--- language: - en library_name: transformers license: cc-by-nc-4.0 quantized_by: mradermacher --- ## About weighted/imatrix quants of https://huggingface.co/Sao10K/Fimbulvetr-11B-v2 ## 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-i1-GGUF/resolve/main/Fimbulvetr-11B-v2.i1-IQ1_S.gguf) | i1-IQ1_S | 2.6 | | | [GGUF](https://huggingface.co/mradermacher/Fimbulvetr-11B-v2-i1-GGUF/resolve/main/Fimbulvetr-11B-v2.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 3.2 | | | [GGUF](https://huggingface.co/mradermacher/Fimbulvetr-11B-v2-i1-GGUF/resolve/main/Fimbulvetr-11B-v2.i1-IQ2_XS.gguf) | i1-IQ2_XS | 3.5 | | | [GGUF](https://huggingface.co/mradermacher/Fimbulvetr-11B-v2-i1-GGUF/resolve/main/Fimbulvetr-11B-v2.i1-IQ2_S.gguf) | i1-IQ2_S | 3.7 | | | [GGUF](https://huggingface.co/mradermacher/Fimbulvetr-11B-v2-i1-GGUF/resolve/main/Fimbulvetr-11B-v2.i1-IQ2_M.gguf) | i1-IQ2_M | 3.9 | | | [GGUF](https://huggingface.co/mradermacher/Fimbulvetr-11B-v2-i1-GGUF/resolve/main/Fimbulvetr-11B-v2.i1-Q2_K.gguf) | i1-Q2_K | 4.3 | IQ3_XXS probably better | | [GGUF](https://huggingface.co/mradermacher/Fimbulvetr-11B-v2-i1-GGUF/resolve/main/Fimbulvetr-11B-v2.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 4.4 | fast, lower quality | | [GGUF](https://huggingface.co/mradermacher/Fimbulvetr-11B-v2-i1-GGUF/resolve/main/Fimbulvetr-11B-v2.i1-IQ3_XS.gguf) | i1-IQ3_XS | 4.7 | | | [GGUF](https://huggingface.co/mradermacher/Fimbulvetr-11B-v2-i1-GGUF/resolve/main/Fimbulvetr-11B-v2.i1-Q3_K_S.gguf) | i1-Q3_K_S | 4.9 | IQ3_XS probably better | | [GGUF](https://huggingface.co/mradermacher/Fimbulvetr-11B-v2-i1-GGUF/resolve/main/Fimbulvetr-11B-v2.i1-IQ3_S.gguf) | i1-IQ3_S | 4.9 | fast, beats Q3_K* | | [GGUF](https://huggingface.co/mradermacher/Fimbulvetr-11B-v2-i1-GGUF/resolve/main/Fimbulvetr-11B-v2.i1-IQ3_M.gguf) | i1-IQ3_M | 5.1 | | | [GGUF](https://huggingface.co/mradermacher/Fimbulvetr-11B-v2-i1-GGUF/resolve/main/Fimbulvetr-11B-v2.i1-Q3_K_M.gguf) | i1-Q3_K_M | 5.5 | IQ3_S probably better | | [GGUF](https://huggingface.co/mradermacher/Fimbulvetr-11B-v2-i1-GGUF/resolve/main/Fimbulvetr-11B-v2.i1-Q3_K_L.gguf) | i1-Q3_K_L | 5.9 | IQ3_M probably better | | [GGUF](https://huggingface.co/mradermacher/Fimbulvetr-11B-v2-i1-GGUF/resolve/main/Fimbulvetr-11B-v2.i1-Q4_K_S.gguf) | i1-Q4_K_S | 6.4 | almost as good as Q4_K_M | | [GGUF](https://huggingface.co/mradermacher/Fimbulvetr-11B-v2-i1-GGUF/resolve/main/Fimbulvetr-11B-v2.i1-Q4_K_M.gguf) | i1-Q4_K_M | 6.7 | fast, medium quality | | [GGUF](https://huggingface.co/mradermacher/Fimbulvetr-11B-v2-i1-GGUF/resolve/main/Fimbulvetr-11B-v2.i1-Q5_K_S.gguf) | i1-Q5_K_S | 7.7 | | | [GGUF](https://huggingface.co/mradermacher/Fimbulvetr-11B-v2-i1-GGUF/resolve/main/Fimbulvetr-11B-v2.i1-Q5_K_M.gguf) | i1-Q5_K_M | 7.9 | best weighted quant | 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