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README.md

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-weighted/imatrix quants of https://huggingface.co/NousResearch/Nous-Hermes-2-Yi-34B
+---
+base_model: 01-ai/Yi-34B
+datasets:
+- teknium/OpenHermes-2.5
+language:
+- en
+library_name: transformers
+license: apache-2.0
+quantized_by: mradermacher
+tags:
+- yi
+- instruct
+- finetune
+- chatml
+- gpt4
+- synthetic data
+- distillation
+---
+## About
+
+weighted/imatrix quants of https://huggingface.co/NousResearch/Nous-Hermes-2-Yi-34B
+
+<!-- provided-files -->
+## 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/Nous-Hermes-2-Yi-34B-i1-GGUF/resolve/main/Nous-Hermes-2-Yi-34B.i1-IQ2_M.gguf) | i1-IQ2_M | 12.5 |  |
+| [GGUF](https://huggingface.co/mradermacher/Nous-Hermes-2-Yi-34B-i1-GGUF/resolve/main/Nous-Hermes-2-Yi-34B.i1-Q2_K.gguf) | i1-Q2_K | 13.5 | IQ3_XXS probably better |
+| [GGUF](https://huggingface.co/mradermacher/Nous-Hermes-2-Yi-34B-i1-GGUF/resolve/main/Nous-Hermes-2-Yi-34B.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 14.0 | fast, lower quality |
+| [GGUF](https://huggingface.co/mradermacher/Nous-Hermes-2-Yi-34B-i1-GGUF/resolve/main/Nous-Hermes-2-Yi-34B.i1-IQ3_XS.gguf) | i1-IQ3_XS | 14.8 |  |
+| [GGUF](https://huggingface.co/mradermacher/Nous-Hermes-2-Yi-34B-i1-GGUF/resolve/main/Nous-Hermes-2-Yi-34B.i1-Q3_K_S.gguf) | i1-Q3_K_S | 15.6 | IQ3_XS probably better |
+| [GGUF](https://huggingface.co/mradermacher/Nous-Hermes-2-Yi-34B-i1-GGUF/resolve/main/Nous-Hermes-2-Yi-34B.i1-IQ3_S.gguf) | i1-IQ3_S | 15.7 | fast, beats Q3_K* |
+| [GGUF](https://huggingface.co/mradermacher/Nous-Hermes-2-Yi-34B-i1-GGUF/resolve/main/Nous-Hermes-2-Yi-34B.i1-Q3_K_M.gguf) | i1-Q3_K_M | 17.3 | IQ3_S probably better |
+| [GGUF](https://huggingface.co/mradermacher/Nous-Hermes-2-Yi-34B-i1-GGUF/resolve/main/Nous-Hermes-2-Yi-34B.i1-Q3_K_L.gguf) | i1-Q3_K_L | 18.8 | IQ3_M probably better |
+| [GGUF](https://huggingface.co/mradermacher/Nous-Hermes-2-Yi-34B-i1-GGUF/resolve/main/Nous-Hermes-2-Yi-34B.i1-Q4_K_S.gguf) | i1-Q4_K_S | 20.2 | almost as good as Q4_K_M |
+| [GGUF](https://huggingface.co/mradermacher/Nous-Hermes-2-Yi-34B-i1-GGUF/resolve/main/Nous-Hermes-2-Yi-34B.i1-Q4_K_M.gguf) | i1-Q4_K_M | 21.3 | fast, medium quality |
+| [GGUF](https://huggingface.co/mradermacher/Nous-Hermes-2-Yi-34B-i1-GGUF/resolve/main/Nous-Hermes-2-Yi-34B.i1-Q5_K_S.gguf) | i1-Q5_K_S | 24.3 |  |
+| [GGUF](https://huggingface.co/mradermacher/Nous-Hermes-2-Yi-34B-i1-GGUF/resolve/main/Nous-Hermes-2-Yi-34B.i1-Q5_K_M.gguf) | i1-Q5_K_M | 25.0 | 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
+
+<!-- end -->