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…
Repository Files & Downloads
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| Browse files on Hugging Face | ||||
Model Details
| Model ID | mradermacher/MELT-llama-2-3x70b-chat-hf-GGUF |
|---|---|
| Author | mradermacher |
| Pipeline | — |
| License | apache-2.0 |
| Base model | Kentucky-Open-Science/MELT-llama-2-3x70b-chat-hf |
| Last modified | 2026-08-28T23:26:03.000Z |
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):
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.
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