Quantized Mcqa Model by beam-searchers

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  Arxiv:1910.09700   4-bit   Autotrain compatible   Conversational   Endpoints compatible   Gptq   Llama   Lora   Region:us   Safetensors   Sharded   Tensorflow   Unsloth

Quantized Mcqa Model Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Quantized Mcqa Model (beam-searchers/quantized_mcqa_model)

Quantized Mcqa Model Parameters and Internals

LLM NameQuantized Mcqa Model
Repository ๐Ÿค—https://huggingface.co/beam-searchers/quantized_mcqa_model 
Model Size2b
Required VRAM5.8 GB
Updated2024-12-22
Maintainerbeam-searchers
Model Files  0.2 GB   4.7 GB: 1-of-2   1.1 GB: 2-of-2
Model ArchitectureAutoModelForCausalLM
Model Max Length8192
Is Biasednone
Tokenizer ClassPreTrainedTokenizerFast
Padding Token<|reserved_special_token_250|>
PEFT TypeLORA
LoRA ModelYes
PEFT Target Modulesv_proj|up_proj|o_proj|k_proj|down_proj|q_proj|gate_proj
LoRA Alpha16
LoRA Dropout0
R Param16

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Note: green Score (e.g. "73.2") means that the model is better than beam-searchers/quantized_mcqa_model.

Rank the Quantized Mcqa Model 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 v20241217