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mradermacher/MELT-llama-2-3x70b-chat-hf-GGUF overview

About < quantize version: 2 < output tensor quantised: 1 < convert type: < vocab type: static quants of https://huggingface.co/Kentucky Open Science/MELT llama…

transformersenbase_model:Kentucky-Open-Science/MELT-llama-2-3x70b-chat-hfbase_model:finetune:Kentucky-Open-Science/MELT-llama-2-3x70b-chat-hflicense:apache-2.0endpoints_compatibleregion:us
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Model Details

Model IDmradermacher/MELT-llama-2-3x70b-chat-hf-GGUF
Authormradermacher
Pipeline
Licenseapache-2.0
Base modelKentucky-Open-Science/MELT-llama-2-3x70b-chat-hf
Last modified2026-08-28T23:26:03.000Z

Model README

---

base_model: Kentucky-Open-Science/MELT-llama-2-3x70b-chat-hf

language:

  • en

library_name: transformers

license: apache-2.0

mradermacher:

readme_rev: 1

quantized_by: mradermacher

---

About

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

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

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

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

static quants of https://huggingface.co/Kentucky-Open-Science/MELT-llama-2-3x70b-chat-hf

<!-- provided-files -->

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

weighted/imatrix quants are available at https://huggingface.co/mradermacher/MELT-llama-2-3x70b-chat-hf-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 |

|:-----|:-----|--------:|:------|

| PART 1 PART 2 | Q2_K | 66.4 | |

| PART 1 PART 2 | IQ3_XS | 74.2 | |

| PART 1 PART 2 | IQ3_S | 78.5 | beats Q3_K* |

| PART 1 PART 2 | Q3_K_S | 78.5 | |

| PART 1 PART 2 | IQ3_M | 80.1 | |

| PART 1 PART 2 | Q3_K_M | 87.1 | lower quality |

| PART 1 PART 2 | Q3_K_L | 94.4 | |

| PART 1 PART 2 | IQ4_XS | 97.9 | |

| PART 1 PART 2 PART 3 | Q4_K_S | 103.4 | fast, recommended |

| PART 1 PART 2 PART 3 | Q4_K_M | 109.8 | fast, recommended |

| PART 1 PART 2 PART 3 | Q5_K_S | 125.1 | |

| PART 1 PART 2 PART 3 | Q5_K_M | 128.9 | |

| PART 1 PART 2 PART 3 PART 4 | Q6_K | 149.2 | very good quality |

| PART 1 PART 2 PART 3 PART 4 | Q8_0 | 193.2 | fast, best quality |

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.

<!-- end -->

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