--- exported_from: ParasiticRogue/Nyakura-CausalLM-RP-34B language: - en library_name: transformers license: other license_link: https://huggingface.co/01-ai/Yi-34B-200K/blob/main/LICENSE license_name: yi-34b quantized_by: mradermacher tags: - mergekit - merge --- ## About weighted/imatrix quants of https://huggingface.co/ParasiticRogue/Nyakura-CausalLM-RP-34B static quants are available at https://huggingface.co/mradermacher/Nyakura-CausalLM-RP-34B-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/Nyakura-CausalLM-RP-34B-i1-GGUF/resolve/main/Nyakura-CausalLM-RP-34B.i1-IQ2_M.gguf) | i1-IQ2_M | 11.9 | | | [GGUF](https://huggingface.co/mradermacher/Nyakura-CausalLM-RP-34B-i1-GGUF/resolve/main/Nyakura-CausalLM-RP-34B.i1-Q2_K.gguf) | i1-Q2_K | 12.9 | IQ3_XXS probably better | | [GGUF](https://huggingface.co/mradermacher/Nyakura-CausalLM-RP-34B-i1-GGUF/resolve/main/Nyakura-CausalLM-RP-34B.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 13.4 | lower quality | | [GGUF](https://huggingface.co/mradermacher/Nyakura-CausalLM-RP-34B-i1-GGUF/resolve/main/Nyakura-CausalLM-RP-34B.i1-Q3_K_S.gguf) | i1-Q3_K_S | 15.1 | IQ3_XS probably better | | [GGUF](https://huggingface.co/mradermacher/Nyakura-CausalLM-RP-34B-i1-GGUF/resolve/main/Nyakura-CausalLM-RP-34B.i1-Q3_K_M.gguf) | i1-Q3_K_M | 16.8 | IQ3_S probably better | | [GGUF](https://huggingface.co/mradermacher/Nyakura-CausalLM-RP-34B-i1-GGUF/resolve/main/Nyakura-CausalLM-RP-34B.i1-Q3_K_L.gguf) | i1-Q3_K_L | 18.2 | IQ3_M probably better | | [GGUF](https://huggingface.co/mradermacher/Nyakura-CausalLM-RP-34B-i1-GGUF/resolve/main/Nyakura-CausalLM-RP-34B.i1-IQ4_XS.gguf) | i1-IQ4_XS | 18.6 | | | [GGUF](https://huggingface.co/mradermacher/Nyakura-CausalLM-RP-34B-i1-GGUF/resolve/main/Nyakura-CausalLM-RP-34B.i1-Q4_K_S.gguf) | i1-Q4_K_S | 19.7 | optimal size/speed/quality | | [GGUF](https://huggingface.co/mradermacher/Nyakura-CausalLM-RP-34B-i1-GGUF/resolve/main/Nyakura-CausalLM-RP-34B.i1-Q4_K_M.gguf) | i1-Q4_K_M | 20.8 | fast, recommended | | [GGUF](https://huggingface.co/mradermacher/Nyakura-CausalLM-RP-34B-i1-GGUF/resolve/main/Nyakura-CausalLM-RP-34B.i1-Q5_K_S.gguf) | i1-Q5_K_S | 23.8 | | | [GGUF](https://huggingface.co/mradermacher/Nyakura-CausalLM-RP-34B-i1-GGUF/resolve/main/Nyakura-CausalLM-RP-34B.i1-Q6_K.gguf) | i1-Q6_K | 28.3 | practically like static Q6_K | 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.