base_model: sequelbox/Ministral-3-14B-Reasoning-2512-PlumEsper1.1
datasets:
- sequelbox/Celestia3-DeepSeek-R1-0528
- sequelbox/Mitakihara-DeepSeek-R1-0528
- sequelbox/Raiden-DeepSeek-R1
- sequelbox/Titanium3-DeepSeek-V3.1-Terminus
- sequelbox/Tachibana3-Part1-DeepSeek-V3.1-Terminus
- sequelbox/Tachibana3-Part2-DeepSeek-V3.2
language:
- en
library_name: transformers
mradermacher:
readme_rev: 1
quantized_by: mradermacher
tags:
- mergekit
- merge
- esper
- shining-valiant
- valiant
- mistral3
- mistral
- mistral-common
- ministral-3-14b
- ministral
- reasoning
- code
- code-reasoning
- code-instruct
- python
- javascript
- dev-ops
- jenkins
- terraform
- scripting
- powershell
- azure
- aws
- gcp
- cloud
- science
- science-reasoning
- physics
- biology
- chemistry
- earth-science
- astronomy
- machine-learning
- artificial-intelligence
- compsci
- computer-science
- information-theory
- ML-Ops
- math
- cuda
- deep-learning
- transformers
- agentic
- LLM
- neuromorphic
- self-improvement
- complex-systems
- cognition
- linguistics
- philosophy
- logic
- epistemology
- simulation
- game-theory
- knowledge-management
- creativity
- problem-solving
- architect
- engineer
- developer
- creative
- analytical
- expert
- rationality
- conversational
- chat
- instruct
About
static quants of https://huggingface.co/sequelbox/Ministral-3-14B-Reasoning-2512-PlumEsper1.1
For a convenient overview and download list, visit our model page for this model.
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
Usage
If you are unsure how to use GGUF files, refer to one of TheBloke's READMEs 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 | mmproj-Q8_0 | 0.6 | multi-modal supplement |
| GGUF | mmproj-f16 | 1.0 | multi-modal supplement |
| GGUF | Q2_K | 5.3 | |
| GGUF | Q3_K_S | 6.2 | |
| GGUF | Q3_K_M | 6.8 | lower quality |
| GGUF | Q3_K_L | 7.3 | |
| GGUF | IQ4_XS | 7.6 | |
| GGUF | Q4_K_S | 7.9 | fast, recommended |
| GGUF | Q4_K_M | 8.3 | fast, recommended |
| GGUF | Q5_K_S | 9.5 | |
| GGUF | Q5_K_M | 9.7 | |
| GGUF | Q6_K | 11.2 | very good quality |
| GGUF | Q8_0 | 14.5 | 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.