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Zephyr 7B Beta 5.0bpw EXL2 by aspirina765

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Zephyr 7B Beta 5.0bpw EXL2 is an open-source language model by aspirina765. Features: 7b LLM, VRAM: 14.4GB, Context: 32K, License: mit, Quantized, LLM Explorer Score: 0.14.

  Arxiv:2305.18290   Arxiv:2310.16944 Base model:finetune:mistralai/... Base model:mistralai/mistral-7...   Conversational Dataset:huggingfaceh4/ultracha... Dataset:huggingfaceh4/ultrafee...   En   Endpoints compatible   Exl2   Generated from trainer   Mistral   Model-index   Pytorch   Quantized   Region:us   Safetensors   Sharded
Model Card on HF 🤗: https://huggingface.co/aspirina765/zephyr-7b-beta-5.0bpw-exl2 

Zephyr 7B Beta 5.0bpw EXL2 Benchmarks

LLME Score: 0.14155
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 5.0bpw EXL2 (aspirina765/zephyr-7b-beta-5.0bpw-exl2)
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Zephyr 7B Beta 5.0bpw EXL2 Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
chat
Primary Use Cases:
Friendly chatbot, Pirate chatbot example
Limitations:
Model can produce problematic outputs when prompted to do so., Lacks fine-tuning for safety using RLHF
Considerations:
The model has not been aligned to human preferences for safety within the RLHF phase.
Additional Notes 
Removing in-built alignment boosted performance but increases the possibility of generating problematic text.
Supported Languages 
en (Primarily English)
Training Details 
Data Sources:
UltraChat, UltraFeedback
Methodology:
Direct Preference Optimization (DPO)
Model Architecture:
GPT-like
Input Output 
Input Format:
Expected input format is set up using a chat template
Accepted Modalities:
text
LLM NameZephyr 7B Beta 5.0bpw EXL2
Repository 🤗https://huggingface.co/aspirina765/zephyr-7b-beta-5.0bpw-exl2 
Base Model(s)  mistralai/Mistral-7B-v0.1   mistralai/Mistral-7B-v0.1
Model Size7b
Required VRAM14.4 GB
Updated2026-04-04
Maintaineraspirina765
Model Typemistral
Model Files  0.0 GB   1.7 GB   4.7 GB   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   0.0 GB
Supported Languagesen
Quantization Typeexl2
Model ArchitectureMistralForCausalLM
Licensemit
Context Length32768
Model Max Length32768
Transformers Version4.35.0
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typebfloat16

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Mistral 7B Instruct V0.2 Fp1632K / 14.4 GB260
Mistral 7B Instruct V0.2 4bit32K / 4.3 GB1331
...tral 7B Instruct V0.3 Bnb 4bit32K / 4.1 GB3043728
Mistral 7B Instruct V0.2 8bit32K / 7.6 GB41
...tral 7B Instruct V0.2 Bnb 4bit32K / 4.1 GB1256736
Mixtral V0.3 Full 16bit32K / 14.5 GB60
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Note: green Score (e.g. "73.2") means that the model is better than aspirina765/zephyr-7b-beta-5.0bpw-exl2.

Rank the Zephyr 7B Beta 5.0bpw EXL2 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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