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Llama2 7B Finetuned by stuser2023

 »  All LLMs  »  stuser2023  »  Llama2 7B Finetuned   URL Share it on

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Model Card on HF 🤗: https://huggingface.co/stuser2023/Llama2-7b-finetuned 

Llama2 7B Finetuned Benchmarks

LLME Score: 0.14475
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Llama2 7B Finetuned (stuser2023/Llama2-7b-finetuned)

Llama2 7B Finetuned Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
Research
Additional Notes 
The model uses 8-bit quantization with hf's BitsAndBytesConfig.
Supported Languages 
English (Proficient), Chinese (Proficient), Japanese (Proficient), Korean (Proficient)
Training Details 
Data Sources:
https://huggingface.co/datasets/timdettmers/openassistant-guanaco
Methodology:
Fine-tuning using peft library's LoRA method with parameters lora_alpha=16, lora_dropout=0.1, lora_r=8.
Hardware Used:
Google Colab with GPU: T4, 15GB
Input Output 
Input Format:
Prompt with special tokens, e.g., ~~Human: prompt and expected completion ~~Assistant:
Accepted Modalities:
text
Output Format:
Generated text completion
LLM NameLlama2 7B Finetuned
Repository 🤗https://huggingface.co/stuser2023/Llama2-7b-finetuned 
Model Size7b
Required VRAM7.6 GB
Updated2025-02-22
Maintainerstuser2023
Model Files  0.0 GB   5.0 GB: 1-of-2   2.6 GB: 2-of-2   0.0 GB
Model ArchitectureAutoModelForCausalLM
Licenseapache-2.0
Is Biasednone
Tokenizer ClassLlamaTokenizer
Padding Token</s>
PEFT TypeLORA
LoRA ModelYes
PEFT Target Modulesv_proj|q_proj
LoRA Alpha16
LoRA Dropout0.1
R Param8

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Note: green Score (e.g. "73.2") means that the model is better than stuser2023/Llama2-7b-finetuned.

Rank the Llama2 7B Finetuned 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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Release v20241227
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