---
base_model: Delta-Vector/Francois-PE-V2-Huali-12B
datasets:
- PocketDoc/Dans-Personamaxx-VN
- NewEden/LIMARP-Complexity
- NewEden/PIPPA-Mega-Filtered
- NewEden/OpenCAI-ShareGPT
- NewEden/Creative_Writing-Complexity
- NewEden/Light-Novels-Roleplay-Logs-Books-Oh-My-duplicate-turns-removed
- PocketDoc/Dans-Failuremaxx-Adventure-3
- NewEden/Books-V2-ShareGPT
- NewEden/Deepseek-V3-RP-Filtered
- NewEden/BlueSky-10K-Complexity
- NewEden/Final-Alpindale-LNs-ShareGPT
- NewEden/DeepseekRP-Filtered
- NewEden/RP-logs-V2-Experimental
- anthracite-org/kalo_opus_misc_240827
- anthracite-org/kalo_misc_part2
- NewEden/vanilla-backrooms-claude-sharegpt
- NewEden/Storium-Prefixed-Clean
- NewEden/KTO-IF-Dans
- NewEden/KTO-Instruct-Mix
- NewEden/Opus-accepted-hermes-rejected-shuffled
language:
- en
library_name: transformers
mradermacher:
  readme_rev: 1
quantized_by: mradermacher
tags:
- fine-tuning
- prose
- KTO
- axolotl
- finetune
- roleplaying
- creative-writing
---
## About

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weighted/imatrix quants of https://huggingface.co/Delta-Vector/Francois-PE-V2-Huali-12B

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***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Francois-PE-V2-Huali-12B-i1-GGUF).***

static quants are available at https://huggingface.co/mradermacher/Francois-PE-V2-Huali-12B-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://www.modelscope.cn/models/mradermacher/Francois-PE-V2-Huali-12B-i1-GGUF/resolve/master/Francois-PE-V2-Huali-12B.i1-IQ2_XS.gguf) | i1-IQ2_XS | 4.0 |  |
| [GGUF](https://www.modelscope.cn/models/mradermacher/Francois-PE-V2-Huali-12B-i1-GGUF/resolve/master/Francois-PE-V2-Huali-12B.i1-IQ3_XS.gguf) | i1-IQ3_XS | 5.4 |  |
| [GGUF](https://www.modelscope.cn/models/mradermacher/Francois-PE-V2-Huali-12B-i1-GGUF/resolve/master/Francois-PE-V2-Huali-12B.i1-IQ4_XS.gguf) | i1-IQ4_XS | 6.8 |  |
| [GGUF](https://www.modelscope.cn/models/mradermacher/Francois-PE-V2-Huali-12B-i1-GGUF/resolve/master/Francois-PE-V2-Huali-12B.i1-Q4_K_M.gguf) | i1-Q4_K_M | 7.6 | fast, recommended |
| [GGUF](https://www.modelscope.cn/models/mradermacher/Francois-PE-V2-Huali-12B-i1-GGUF/resolve/master/Francois-PE-V2-Huali-12B.i1-Q5_K_M.gguf) | i1-Q5_K_M | 8.8 |  |
| [GGUF](https://www.modelscope.cn/models/mradermacher/Francois-PE-V2-Huali-12B-i1-GGUF/resolve/master/Francois-PE-V2-Huali-12B.i1-Q6_K.gguf) | i1-Q6_K | 10.2 | 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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