---
base_model: Nekochu/Luminia-8B-RP
datasets:
- Nekochu/Luminia-mixture
- UnfilteredAI/DAN
- mpingale/mental-health-chat-dataset
- Amod/mental_health_counseling_conversations
- heliosbrahma/mental_health_chatbot_dataset
- victunes/nart-100k-synthetic-buddy-mixed-names
- Falah/Mental_health_dataset4Fine_Tuning
- EmoCareAI/Psych8k
- samhog/psychology-10k
- Doctor-Shotgun/no-robots-sharegpt
- Gryphe/Opus-WritingPrompts
- NobodyExistsOnTheInternet/ToxicQAFinal
- meseca/opus-instruct-9k
- PJMixers/grimulkan_theory-of-mind-ShareGPT
- CapybaraPure/Decontaminated-ShareGPT
- MinervaAI/Aesir-Preview
- Epiculous/Gnosis
- Norquinal/claude_multiround_chat_30k
- Locutusque/hercules-v5.0
- G-reen/Duet-v0.5
- cgato/SlimOrcaDedupCleaned
- Gryphe/Sonnet3.5-SlimOrcaDedupCleaned
- ChaoticNeutrals/Synthetic-Dark-RP
- ChaoticNeutrals/Synthetic-RP
- ChaoticNeutrals/Luminous_Opus
- kalomaze/Opus_Instruct_25k
language:
- en
library_name: transformers
license: apache-2.0
quantized_by: mradermacher
tags:
- llama-factory
- lora
- not-for-all-audiences
- nsfw
---
## About

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static quants of https://huggingface.co/Nekochu/Luminia-8B-RP

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weighted/imatrix quants are available at https://huggingface.co/mradermacher/Luminia-8B-RP-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 |
|:-----|:-----|--------:|:------|
| [GGUF](https://huggingface.co/mradermacher/Luminia-8B-RP-GGUF/resolve/main/Luminia-8B-RP.Q2_K.gguf) | Q2_K | 3.3 |  |
| [GGUF](https://huggingface.co/mradermacher/Luminia-8B-RP-GGUF/resolve/main/Luminia-8B-RP.Q3_K_S.gguf) | Q3_K_S | 3.8 |  |
| [GGUF](https://huggingface.co/mradermacher/Luminia-8B-RP-GGUF/resolve/main/Luminia-8B-RP.Q3_K_M.gguf) | Q3_K_M | 4.1 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/Luminia-8B-RP-GGUF/resolve/main/Luminia-8B-RP.Q3_K_L.gguf) | Q3_K_L | 4.4 |  |
| [GGUF](https://huggingface.co/mradermacher/Luminia-8B-RP-GGUF/resolve/main/Luminia-8B-RP.IQ4_XS.gguf) | IQ4_XS | 4.6 |  |
| [GGUF](https://huggingface.co/mradermacher/Luminia-8B-RP-GGUF/resolve/main/Luminia-8B-RP.Q4_K_S.gguf) | Q4_K_S | 4.8 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/Luminia-8B-RP-GGUF/resolve/main/Luminia-8B-RP.Q4_K_M.gguf) | Q4_K_M | 5.0 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/Luminia-8B-RP-GGUF/resolve/main/Luminia-8B-RP.Q5_K_S.gguf) | Q5_K_S | 5.7 |  |
| [GGUF](https://huggingface.co/mradermacher/Luminia-8B-RP-GGUF/resolve/main/Luminia-8B-RP.Q5_K_M.gguf) | Q5_K_M | 5.8 |  |
| [GGUF](https://huggingface.co/mradermacher/Luminia-8B-RP-GGUF/resolve/main/Luminia-8B-RP.Q6_K.gguf) | Q6_K | 6.7 | very good quality |
| [GGUF](https://huggingface.co/mradermacher/Luminia-8B-RP-GGUF/resolve/main/Luminia-8B-RP.Q8_0.gguf) | Q8_0 | 8.6 | fast, best quality |
| [GGUF](https://huggingface.co/mradermacher/Luminia-8B-RP-GGUF/resolve/main/Luminia-8B-RP.f16.gguf) | f16 | 16.2 | 16 bpw, overkill |

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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