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Norobara ZLoss 8x7B GPTQ by TheBloke

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  4-bit   Autotrain compatible 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   Gptq   Mixtral   Moe   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/TheBloke/Norobara-ZLoss-8x7B-GPTQ 

Norobara ZLoss 8x7B GPTQ Benchmarks

LLME Score: 0.12704
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 GPTQ (TheBloke/Norobara-ZLoss-8x7B-GPTQ)
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Norobara ZLoss 8x7B GPTQ Parameters and Internals

Model Type 
mixtral
Use Cases 
Limitations:
The model will show biases present in the base model. No ethical alignment was applied to prevent generation of toxic or harmful outputs (in fact the opposite, with examples from toxic-DPO included).
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:
ZLoss and Megablocks-based fork of transformers
Training Time:
13 hours
Hardware Used:
single H100 GPU
Input Output 
Input Format:
### Instruction: {system_message} ### Input: {prompt} ### Response:
LLM NameNorobara ZLoss 8x7B GPTQ
Repository 🤗https://huggingface.co/TheBloke/Norobara-ZLoss-8x7B-GPTQ 
Model NameNorobara ZLoss 8X7B
Model CreatorDoctor Shotgun
Base Model(s)  Norobara ZLoss 8x7B   Doctor-Shotgun/Norobara-ZLoss-8x7B
Model Size6.1b
Required VRAM23.8 GB
Updated2025-09-23
MaintainerTheBloke
Model Typemixtral
Model Files  23.8 GB
Supported Languagesen
GPTQ QuantizationYes
Quantization Typegptq
Model ArchitectureMixtralForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.37.0.dev0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typebfloat16

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