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RichardErkhov/
Alsebay_-_Narisumashi-11B-v1.5-gguf

Name: Alsebay_-_Narisumashi-11B-v1.5-gguf
Availability: InStock

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Narisumashi-11B-v1.5 - GGUF

Model creator: https://huggingface.co/Alsebay/
Original model: https://huggingface.co/Alsebay/Narisumashi-11B-v1.5/

Name	Quant method	Size
Narisumashi-11B-v1.5.Q2_K.gguf	Q2_K	3.73GB
Narisumashi-11B-v1.5.IQ3_XS.gguf	IQ3_XS	4.14GB
Narisumashi-11B-v1.5.IQ3_S.gguf	IQ3_S	4.37GB
Narisumashi-11B-v1.5.Q3_K_S.gguf	Q3_K_S	4.34GB
Narisumashi-11B-v1.5.IQ3_M.gguf	IQ3_M	4.51GB
Narisumashi-11B-v1.5.Q3_K.gguf	Q3_K	4.84GB
Narisumashi-11B-v1.5.Q3_K_M.gguf	Q3_K_M	4.84GB
Narisumashi-11B-v1.5.Q3_K_L.gguf	Q3_K_L	5.26GB
Narisumashi-11B-v1.5.IQ4_XS.gguf	IQ4_XS	5.43GB
Narisumashi-11B-v1.5.Q4_0.gguf	Q4_0	5.66GB
Narisumashi-11B-v1.5.IQ4_NL.gguf	IQ4_NL	5.72GB
Narisumashi-11B-v1.5.Q4_K_S.gguf	Q4_K_S	5.7GB
Narisumashi-11B-v1.5.Q4_K.gguf	Q4_K	6.02GB
Narisumashi-11B-v1.5.Q4_K_M.gguf	Q4_K_M	6.02GB
Narisumashi-11B-v1.5.Q4_1.gguf	Q4_1	6.27GB
Narisumashi-11B-v1.5.Q5_0.gguf	Q5_0	6.89GB
Narisumashi-11B-v1.5.Q5_K_S.gguf	Q5_K_S	6.89GB
Narisumashi-11B-v1.5.Q5_K.gguf	Q5_K	7.08GB
Narisumashi-11B-v1.5.Q5_K_M.gguf	Q5_K_M	7.08GB
Narisumashi-11B-v1.5.Q5_1.gguf	Q5_1	7.51GB
Narisumashi-11B-v1.5.Q6_K.gguf	Q6_K	8.2GB
Narisumashi-11B-v1.5.Q8_0.gguf	Q8_0	10.62GB

Original model description:

language:

en license: cc-by-nc-4.0 tags:
text-generation-inference
transformers
unsloth
llama
trl
sft
Roleplay
roleplay base_model: Sao10K/Fimbulvetr-11B-v2

About this model

TSF content

Beta for V2 of https://huggingface.co/Alsebay/Narumashi-11B-v0.9 (wrong typo but I'm too lazy to fix), but have only 32 rank and 32 lora rank, which cause the model didn't learn well all dataset information, it just know basis information. Anyways, it good if your have a chinese, japanese prompt to trigger TSF content. Maybe not smart, I haven't test yet.

Finetuned from model : Sao10K/Fimbulvetr-11B-v2 . Thank Sao10K a lot :)

I have text and found that Sao10K/Fimbulvetr-11B-v2 could unlock as 8K context length (maybe logic will go down a bit?), so I leave it alone to reduce RAM and VRAM. That mean you can use as 8k context length although this model say only 4k.

GGUF version? here is it.

Dataset

All chinese novels dataset

Dataset(all are novels):
60% skinsuit
25% possession
5% transform(shapeshift)
10% other

Thank Unsloth for good finetuning tool. This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.

RichardErkhov/Alsebay_-_Narisumashi-11B-v1.5-gguf