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Zephyr 7B Alpha GPTQ by anezatra

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  Adapter Base model:adapter:thebloke/ze... Base model:thebloke/zephyr-7b-... Dataset:bitext/bitext-customer...   Finetuned   Generated from trainer   Gptq   Lora   Peft   Quantized   Region:us   Safetensors   Sft   Tensorboard   Trl

Zephyr 7B Alpha GPTQ Benchmarks

LLME Score: 0.19536
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Zephyr 7B Alpha GPTQ Parameters and Internals

Model Type 
text-generation
Additional Notes 
Large language models have been fine-tuned using hyperparameters such as learning_rate: 0.0002, train_batch_size: 8, eval_batch_size: 8, seed: 42, optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08, lr_scheduler_type: cosine, and training_steps: 250 with mixed_precision_training: Native AMP.
Training Details 
Data Sources:
bitext/Bitext-customer-support-llm-chatbot-training-dataset
Methodology:
Fine-tuning
LLM NameZephyr 7B Alpha GPTQ
Repository 🤗https://huggingface.co/anezatra/zephyr-7B-alpha-GPTQ 
Base Model(s)  Zephyr 7B Alpha GPTQ   TheBloke/zephyr-7B-alpha-GPTQ
Model Size7b
Required VRAM0 GB
Updated2024-11-21
Maintaineranezatra
Model Files  0.0 GB   0.0 GB
GPTQ QuantizationYes
Quantization Typegptq
Model ArchitectureAdapter
Licensemit
Is Biasednone
Tokenizer ClassLlamaTokenizer
Padding Token</s>
PEFT TypeLORA
LoRA ModelYes
PEFT Target Modulesv_proj|q_proj
LoRA Alpha16
LoRA Dropout0.05
R Param16
Zephyr 7B Alpha GPTQ (anezatra/zephyr-7B-alpha-GPTQ)

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Note: green Score (e.g. "73.2") means that the model is better than anezatra/zephyr-7B-alpha-GPTQ.

Rank the Zephyr 7B Alpha GPTQ Capabilities

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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 v20241110
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