Norobara ZLoss 8x7B By Doctor-Shotgun: Benchmarks, Features and Detailed Analysis. Insights on Norobara ZLoss 8x7B.

Autotrain compatible 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 Mixtral Moe Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Doctor-Shotgun/Norobara-ZLoss-8x7B

Norobara ZLoss 8x7B Benchmarks

LLME Score: 0.12709

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

Norobara ZLoss 8x7B (Doctor-Shotgun/Norobara-ZLoss-8x7B)

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Norobara ZLoss 8x7B Parameters and Internals

Model Type

text-generation

Use Cases

Limitations:

Model may generate toxic or harmful outputs.

Considerations:

Generate at your own risk.

Additional Notes

This is an experimental instruct-tuned model to test various loss implementations.

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:

Trained using ZLoss and Megablocks-based fork of transformers.

Training Time:

3 epochs, 13 hours using a single H100 GPU

Hardware Used:

single H100 GPU

Safety Evaluation

Risk Categories:

bias, toxic output

Ethical Considerations:

Model may generate toxic or harmful outputs.

Input Output

Input Format:

Modified multi-turn Alpaca instruction format

LLM Name	Norobara ZLoss 8x7B
Repository 🤗	https://huggingface.co/Doctor-Shotgun/Norobara-ZLoss-8x7B
Model Size	46.7b
Required VRAM	93.6 GB
Updated	2025-10-11
Maintainer	Doctor-Shotgun
Model Type	mixtral
Model Files	4.9 GB: 1-of-19 5.0 GB: 2-of-19 5.0 GB: 3-of-19 4.9 GB: 4-of-19 5.0 GB: 5-of-19 5.0 GB: 6-of-19 4.9 GB: 7-of-19 5.0 GB: 8-of-19 5.0 GB: 9-of-19 4.9 GB: 10-of-19 5.0 GB: 11-of-19 5.0 GB: 12-of-19 5.0 GB: 13-of-19 4.9 GB: 14-of-19 5.0 GB: 15-of-19 5.0 GB: 16-of-19 4.9 GB: 17-of-19 5.0 GB: 18-of-19 4.2 GB: 19-of-19
Supported Languages	en
Model Architecture	MixtralForCausalLM
Context Length	32768
Model Max Length	32768
Transformers Version	4.36.2
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	bfloat16

Quantized Models of the Norobara ZLoss 8x7B

Model	Likes	Downloads	VRAM
Norobara ZLoss 8x7B GGUF	2	224	15 GB
Norobara ZLoss 8x7B AWQ	3	7	24 GB
Norobara ZLoss 8x7B GPTQ	2	4	23 GB

Best Alternatives to Norobara ZLoss 8x7B

Best Alternatives	Context / RAM	Downloads	Likes
Mixtral 8x7B Instruct V0.1	32K / 93.6 GB	481112	4637
Nous Hermes 2 Mixtral 8x7B DPO	32K / 93.6 GB	14686	451
Mixtral 8x7B V0.1	32K / 93.6 GB	61735	1788
Sensualize Mixtral Bf16	32K / 93.6 GB	0	0
Skadi Mixtral V1	32K / 93.5 GB	0	0
Franziska Mixtral V1	32K / 93.5 GB	0	0
Typhon Mixtral V1	32K / 93.4 GB	0	0
GritLM 8x7B KTO	32K / 93.6 GB	8289	3
Smaug Mixtral V0.1	32K / 187.7 GB	8548	12
NatureLM 8x7B	32K / 0.3 GB	72	18

Note: green Score (e.g. "73.2") means that the model is better than Doctor-Shotgun/Norobara-ZLoss-8x7B.

Rank the Norobara ZLoss 8x7B Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

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

Release v20241124

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