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RichardErkhov/
KoboldAI_-_Mistral-7B-Erebus-v3-gguf

Name: KoboldAI_-_Mistral-7B-Erebus-v3-gguf
Availability: InStock

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gguf

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Quantization made by Richard Erkhov.

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Mistral-7B-Erebus-v3 - GGUF

Model creator: https://huggingface.co/KoboldAI/
Original model: https://huggingface.co/KoboldAI/Mistral-7B-Erebus-v3/

Name	Quant method	Size
Mistral-7B-Erebus-v3.Q2_K.gguf	Q2_K	2.53GB
Mistral-7B-Erebus-v3.IQ3_XS.gguf	IQ3_XS	2.81GB
Mistral-7B-Erebus-v3.IQ3_S.gguf	IQ3_S	2.96GB
Mistral-7B-Erebus-v3.Q3_K_S.gguf	Q3_K_S	2.95GB
Mistral-7B-Erebus-v3.IQ3_M.gguf	IQ3_M	3.06GB
Mistral-7B-Erebus-v3.Q3_K.gguf	Q3_K	3.28GB
Mistral-7B-Erebus-v3.Q3_K_M.gguf	Q3_K_M	3.28GB
Mistral-7B-Erebus-v3.Q3_K_L.gguf	Q3_K_L	3.56GB
Mistral-7B-Erebus-v3.IQ4_XS.gguf	IQ4_XS	3.67GB
Mistral-7B-Erebus-v3.Q4_0.gguf	Q4_0	3.83GB
Mistral-7B-Erebus-v3.IQ4_NL.gguf	IQ4_NL	3.87GB
Mistral-7B-Erebus-v3.Q4_K_S.gguf	Q4_K_S	3.86GB
Mistral-7B-Erebus-v3.Q4_K.gguf	Q4_K	4.07GB
Mistral-7B-Erebus-v3.Q4_K_M.gguf	Q4_K_M	4.07GB
Mistral-7B-Erebus-v3.Q4_1.gguf	Q4_1	4.24GB
Mistral-7B-Erebus-v3.Q5_0.gguf	Q5_0	4.65GB
Mistral-7B-Erebus-v3.Q5_K_S.gguf	Q5_K_S	4.65GB
Mistral-7B-Erebus-v3.Q5_K.gguf	Q5_K	4.78GB
Mistral-7B-Erebus-v3.Q5_K_M.gguf	Q5_K_M	4.78GB
Mistral-7B-Erebus-v3.Q5_1.gguf	Q5_1	5.07GB
Mistral-7B-Erebus-v3.Q6_K.gguf	Q6_K	5.53GB
Mistral-7B-Erebus-v3.Q8_0.gguf	Q8_0	7.17GB

Original model description:

license: apache-2.0 language:

en pipeline_tag: text-generation inference: false tags:
pytorch
mistral
finetuned
not-for-all-audiences

Mistral-7B-Erebus

Model description

This is the third generation of the original Shinen made by Mr. Seeker. The full dataset consists of 8 different sources, all surrounding the "Adult" theme. The name "Erebus" comes from the greek mythology, also named "darkness". This is in line with Shin'en, or "deep abyss". For inquiries, please contact the KoboldAI community. Warning: THIS model is NOT suitable for use by minors. The model will output X-rated content.

Training procedure

Mistral-7B-Erebus was trained on 8x A6000 Ada GPU's for a single epoch. No special frameworks have been used.

Training data

The data can be divided in 8 different datasets:

Literotica (everything with 3.0/5 or higher)
Sexstories (everything with 70 or higher)
Dataset-G (private dataset of X-rated stories)
Doc's Lab (all stories)
Lushstories (Editor's pick)
Swinglifestyle (all stories)
Pike-v2 Dataset (novels with "adult" rating)
SoFurry (collection of various animals)

The dataset uses [Genre: <comma-separated list of genres>] for tagging.

The full dataset is 2.3B tokens in size.

Limitations and biases

Based on known problems with NLP technology, potential relevant factors include bias (gender, profession, race and religion). Warning: This model has a very strong NSFW bias!

RichardErkhov/KoboldAI_-_Mistral-7B-Erebus-v3-gguf