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Llama 2 7B Absa by Orkhan

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  Autotrain compatible   Code   En   Endpoints compatible   Llama   Lora   Pytorch   Region:us   Sharded
Model Card on HF 🤗: https://huggingface.co/Orkhan/llama-2-7b-absa 

Llama 2 7B Absa Benchmarks

LLME Score: 0.12346
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Llama 2 7B Absa (Orkhan/llama-2-7b-absa)

Llama 2 7B Absa Parameters and Internals

Model Type 
text-generation
Use Cases 
Areas:
Aspect-Based Sentiment Analysis
Primary Use Cases:
Identifying aspects in sentences, Analyzing sentiment
Limitations:
Model trained on sentences, not on paragraphs
Additional Notes 
Model fits in a free Google Colab Notebook.
Training Details 
Data Volume:
2000 sentences
Methodology:
Fine-tuning
Input Output 
Input Format:
Sentences
Accepted Modalities:
text
Output Format:
Aspects, opinions, sentiments, and phrases
Performance Tips:
Model generalizes well, suitable for diverse applications
LLM NameLlama 2 7B Absa
Repository 🤗https://huggingface.co/Orkhan/llama-2-7b-absa 
Model Size7b
Required VRAM13.5 GB
Updated2025-03-18
MaintainerOrkhan
Model Files  0.1 GB   10.0 GB: 1-of-2   3.5 GB: 2-of-2
Supported Languagesen
Model ArchitectureAutoModelForCausalLM
Licenseapache-2.0
Is Biasednone
Tokenizer ClassLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
PEFT TypeLORA
LoRA ModelYes
PEFT Target Modulesq_proj|v_proj
LoRA Alpha16
LoRA Dropout0.1
R Param64

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Note: green Score (e.g. "73.2") means that the model is better than Orkhan/llama-2-7b-absa.

Rank the Llama 2 7B Absa 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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