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Zephyr 7B Beta by HuggingFaceH4

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  615879   
  Arxiv:2305.14233   Arxiv:2305.18290   Arxiv:2310.01377   Arxiv:2310.16944   Autotrain compatible Base model:finetune:mistralai/... Base model:mistralai/mistral-7...   Conversational Dataset:huggingfaceh4/ultracha... Dataset:huggingfaceh4/ultrafee...   En   Endpoints compatible   Generated from trainer   Mistral   Model-index   Pytorch   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/HuggingFaceH4/zephyr-7b-beta 

Zephyr 7B Beta Benchmarks

LMSys ELO: 1053 vs 1272 (so35)-17.2%
MMLU Pro: 19.79
GPQA: 5.37
MUSR: 7.73
BBH: 21.49
IFEval: 49.5 vs 88 (so35)-43.8%
ARC: 62.03 vs 96.7 (so35)-35.9%
HellaSwag: 84.53 vs 95.3 (gpt4)-11.3%
MMLU: 61.06 vs 88.3 (so35)-30.8%
TruthfulQA: 57.44 vs 59 (gpt4)-2.6%
WinoGrande: 78.06 vs 87.5 (gpt4)-10.8%
GSM8K: 11.37 vs 96.4 (so35)-88.2%
MATH Lvl 5: 2.87
LLME Score: 0.44031
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Zephyr 7B Beta (HuggingFaceH4/zephyr-7b-beta)

Zephyr 7B Beta Parameters and Internals

Model Type 
text generation, chatbot
Use Cases 
Areas:
chat
Applications:
assistant
Primary Use Cases:
chatbot applications
Limitations:
not aligned to human preferences for safety within the RLHF phase, can produce problematic outputs when prompted
Additional Notes 
Zephyr-7B-β can produce problematic outputs, especially when prompted, due to the lack of human preference alignment and in-the-loop filtering.
Supported Languages 
en (primary)
Training Details 
Data Sources:
HuggingFaceH4/ultrachat_200k, HuggingFaceH4/ultrafeedback_binarized
Methodology:
Direct Preference Optimization (DPO)
Input Output 
Input Format:
structured message input format (role-based behavior)
Accepted Modalities:
text
Output Format:
text generation output
Performance Tips:
Direct Preference Optimization (DPO) improves performance.
LLM NameZephyr 7B Beta
Repository 🤗https://huggingface.co/HuggingFaceH4/zephyr-7b-beta 
Base Model(s)  mistralai/Mistral-7B-v0.1   mistralai/Mistral-7B-v0.1
Model Size7b
Required VRAM14.4 GB
Updated2025-04-25
MaintainerHuggingFaceH4
Model Typemistral
Model Files  1.9 GB: 1-of-8   1.9 GB: 2-of-8   2.0 GB: 3-of-8   1.9 GB: 4-of-8   2.0 GB: 5-of-8   1.9 GB: 6-of-8   2.0 GB: 7-of-8   0.8 GB: 8-of-8   1.9 GB: 1-of-8   1.9 GB: 2-of-8   2.0 GB: 3-of-8   1.9 GB: 4-of-8   2.0 GB: 5-of-8   1.9 GB: 6-of-8   2.0 GB: 7-of-8   0.8 GB: 8-of-8
Supported Languagesen
Model ArchitectureMistralForCausalLM
Licensemit
Context Length32768
Model Max Length32768
Transformers Version4.35.0
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typebfloat16

Quantized Models of the Zephyr 7B Beta

Model
Likes
Downloads
VRAM
Zephyr 7B Beta Marlin0304 GB
Zephyr 7B Beta GGUF224259063 GB
Dj Zephyr 7B F16 GGUF11114 GB
Dj Zephyr 7B Q5 K M GGUF0125 GB
Zephyr 7B Beta AWQ3830684 GB
Zephyr 7B Beta GPTQ5722974 GB
Zephyr 7B Beta Marlin01264 GB
Zephyr 7B Beta GGUF01092 GB
Zephyr 7B Beta GGUF01433 GB
Zephyr 7B Beta GPTQ1104 GB

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Astral 256K 7B V2250K / 14.4 GB210
Astral 256K 7B250K / 14.4 GB200

Rank the Zephyr 7B Beta 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 v20241227
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