mradermacher/OLMo-2-32B-MeditronFO-i1-GGUF overview

---

base_model: EPFLiGHT/OLMo-2-32B-MeditronFO

datasets:

• EPFLiGHT/fully-open-meditron

language:

• en

library_name: transformers

license: apache-2.0

mradermacher:

readme_rev: 1

quantized_by: mradermacher

tags:

• medical
• clinical
• healthcare
• meditron
• fully-open
• medical-llm

---

About

<!-- ### quantize_version: 2 -->

<!-- ### output_tensor_quantised: 1 -->

<!-- ### convert_type: hf -->

<!-- ### vocab_type: -->

<!-- ### tags: nicoboss -->

<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_K_M Q4_0 IQ3_XS Q4_1 IQ3_S -->

<!-- ### quants_skip: -->

<!-- ### skip_mmproj: -->

weighted/imatrix quants of https://huggingface.co/EPFLiGHT/OLMo-2-32B-MeditronFO

<!-- provided-files -->

For a convenient overview and download list, visit our model page for this model.

static quants are available at https://huggingface.co/mradermacher/OLMo-2-32B-MeditronFO-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 | imatrix | 0.1 | imatrix file (for creating your own quants) |

| GGUF | i1-IQ1_S | 7.1 | for the desperate |

| GGUF | i1-IQ1_M | 7.8 | mostly desperate |

| GGUF | i1-IQ2_XXS | 8.9 | |

| GGUF | i1-IQ2_XS | 9.8 | |

| GGUF | i1-IQ2_S | 10.2 | |

| GGUF | i1-IQ2_M | 11.1 | |

| GGUF | i1-Q2_K_S | 11.3 | very low quality |

| GGUF | i1-Q2_K | 12.1 | IQ3_XXS probably better |

| GGUF | i1-IQ3_XXS | 12.6 | lower quality |

| GGUF | i1-IQ3_XS | 13.5 | |

| GGUF | i1-Q3_K_S | 14.2 | IQ3_XS probably better |

| GGUF | i1-IQ3_S | 14.2 | beats Q3_K* |

| GGUF | i1-IQ3_M | 14.6 | |

| GGUF | i1-Q3_K_M | 15.7 | IQ3_S probably better |

| GGUF | i1-Q3_K_L | 17.0 | IQ3_M probably better |

| GGUF | i1-IQ4_XS | 17.4 | |

| GGUF | i1-Q4_0 | 18.4 | fast, low quality |

| GGUF | i1-Q4_K_S | 18.5 | optimal size/speed/quality |

| GGUF | i1-Q4_K_M | 19.6 | fast, recommended |

| GGUF | i1-Q4_1 | 20.4 | |

| GGUF | i1-Q5_K_S | 22.3 | |

| GGUF | i1-Q5_K_M | 23.0 | |

| GGUF | i1-Q6_K | 26.5 | practically like static Q6_K |

Here is a handy graph by ikawrakow comparing some lower-quality quant

types (lower is better):

!image.png

And here are Artefact2's thoughts on the matter:

https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

FAQ / Model Request

See https://huggingface.co/mradermacher/model_requests for some answers to

questions you might have and/or if you want some other model quantized.

Thanks

I thank my company, nethype GmbH, for letting

me use its servers and providing upgrades to my workstation to enable

this work in my free time. Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.

<!-- end -->