auto-patch README.md

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team mradermacher
2025-10-28 08:38:27 +00:00
committed by system
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---
base_model: hasanbasbunar/Lodos-24B-Instruct-2510
language:
- en
library_name: transformers
license: apache-2.0
mradermacher:
readme_rev: 1
quantized_by: mradermacher
tags:
- text-generation-inference
- transformers
- unsloth
- mistral3
- trl
- sft
---
## About
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weighted/imatrix quants of https://huggingface.co/hasanbasbunar/Lodos-24B-Instruct-2510 weighted/imatrix quants of https://huggingface.co/hasanbasbunar/Lodos-24B-Instruct-2510
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***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Lodos-24B-Instruct-2510-i1-GGUF).***
static quants are available at https://huggingface.co/mradermacher/Lodos-24B-Instruct-2510-GGUF
**This is a vision model - mmproj files (if any) will be in the [static repository](https://huggingface.co/mradermacher/Lodos-24B-Instruct-2510-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/Lodos-24B-Instruct-2510-i1-GGUF/resolve/main/Lodos-24B-Instruct-2510.imatrix.gguf) | imatrix | 0.1 | imatrix file (for creating your own qwuants) |
| [GGUF](https://huggingface.co/mradermacher/Lodos-24B-Instruct-2510-i1-GGUF/resolve/main/Lodos-24B-Instruct-2510.i1-IQ1_M.gguf) | i1-IQ1_M | 5.9 | mostly desperate |
| [GGUF](https://huggingface.co/mradermacher/Lodos-24B-Instruct-2510-i1-GGUF/resolve/main/Lodos-24B-Instruct-2510.i1-IQ2_M.gguf) | i1-IQ2_M | 8.2 | |
| [GGUF](https://huggingface.co/mradermacher/Lodos-24B-Instruct-2510-i1-GGUF/resolve/main/Lodos-24B-Instruct-2510.i1-Q2_K_S.gguf) | i1-Q2_K_S | 8.4 | very low quality |
| [GGUF](https://huggingface.co/mradermacher/Lodos-24B-Instruct-2510-i1-GGUF/resolve/main/Lodos-24B-Instruct-2510.i1-Q2_K.gguf) | i1-Q2_K | 9.0 | IQ3_XXS probably better |
| [GGUF](https://huggingface.co/mradermacher/Lodos-24B-Instruct-2510-i1-GGUF/resolve/main/Lodos-24B-Instruct-2510.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 9.4 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/Lodos-24B-Instruct-2510-i1-GGUF/resolve/main/Lodos-24B-Instruct-2510.i1-Q3_K_S.gguf) | i1-Q3_K_S | 10.5 | IQ3_XS probably better |
| [GGUF](https://huggingface.co/mradermacher/Lodos-24B-Instruct-2510-i1-GGUF/resolve/main/Lodos-24B-Instruct-2510.i1-IQ3_M.gguf) | i1-IQ3_M | 10.8 | |
| [GGUF](https://huggingface.co/mradermacher/Lodos-24B-Instruct-2510-i1-GGUF/resolve/main/Lodos-24B-Instruct-2510.i1-Q3_K_M.gguf) | i1-Q3_K_M | 11.6 | IQ3_S probably better |
| [GGUF](https://huggingface.co/mradermacher/Lodos-24B-Instruct-2510-i1-GGUF/resolve/main/Lodos-24B-Instruct-2510.i1-IQ4_XS.gguf) | i1-IQ4_XS | 12.9 | |
| [GGUF](https://huggingface.co/mradermacher/Lodos-24B-Instruct-2510-i1-GGUF/resolve/main/Lodos-24B-Instruct-2510.i1-Q4_K_S.gguf) | i1-Q4_K_S | 13.6 | optimal size/speed/quality |
| [GGUF](https://huggingface.co/mradermacher/Lodos-24B-Instruct-2510-i1-GGUF/resolve/main/Lodos-24B-Instruct-2510.i1-Q4_K_M.gguf) | i1-Q4_K_M | 14.4 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/Lodos-24B-Instruct-2510-i1-GGUF/resolve/main/Lodos-24B-Instruct-2510.i1-Q6_K.gguf) | i1-Q6_K | 19.4 | 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
## 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](https://www.nethype.de/), for letting
me use its servers and providing upgrades to my workstation to enable
this work in my free time. Additional thanks to [@nicoboss](https://huggingface.co/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.
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