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Norobara ZLoss 8x7B GGUF by TheBloke

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Base model:doctor-shotgun/noro... Base model:quantized:doctor-sh...   Conversational Dataset:doctor-shotgun/capybar... Dataset:doctor-shotgun/no-robo... Dataset:huggingfaceh4/no robot...   Dataset:ldjnr/capybara   Dataset:ldjnr/verified-camel Dataset:unalignment/toxic-dpo-...   En   Gguf   Mixtral   Moe   Quantized   Region:us
Model Card on HF 🤗: https://huggingface.co/TheBloke/Norobara-ZLoss-8x7B-GGUF 

Norobara ZLoss 8x7B GGUF Benchmarks

LLME Score: 0.1308
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Norobara ZLoss 8x7B GGUF (TheBloke/Norobara-ZLoss-8x7B-GGUF)
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Norobara ZLoss 8x7B GGUF Parameters and Internals

Model Type 
mixtral
Additional Notes 
This model is uncensored and was created to test various loss implementations while training Mixtral.
Training Details 
Data Sources:
LDJnr/Capybara, unalignment/toxic-dpo-v0.1, LDJnr/Verified-Camel, HuggingFaceH4/no_robots, Doctor-Shotgun/no-robots-sharegpt, Doctor-Shotgun/capybara-sharegpt
Methodology:
Experimental instruct-tuned using ZLoss and Megablocks-based fork of transformers.
Training Time:
13 hours
Hardware Used:
single H100 GPU
Model Architecture:
QLora adapter
LLM NameNorobara ZLoss 8x7B GGUF
Repository 🤗https://huggingface.co/TheBloke/Norobara-ZLoss-8x7B-GGUF 
Model NameNorobara ZLoss 8X7B
Model CreatorDoctor Shotgun
Base Model(s)  Norobara ZLoss 8x7B   Doctor-Shotgun/Norobara-ZLoss-8x7B
Required VRAM15.6 GB
Updated2025-09-23
MaintainerTheBloke
Model Typemixtral
Model Files  15.6 GB   20.4 GB   26.4 GB   26.4 GB   32.2 GB   32.2 GB   38.4 GB   49.6 GB
Supported Languagesen
GGUF QuantizationYes
Quantization Typegguf
Model ArchitectureAutoModel

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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