Cendol Llama2 7B Inst by indonlp

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  Arxiv:2404.06138   Autotrain compatible   Endpoints compatible   Id   Jv   Llama   Pytorch   Region:us   Sharded   Su

Cendol Llama2 7B Inst Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Cendol Llama2 7B Inst (indonlp/cendol-llama2-7b-inst)
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Cendol Llama2 7B Inst Parameters and Internals

Model Type 
Generative, Large Language Model, Instruction-Tuned
Use Cases 
Areas:
Research
Applications:
Single-turn conversation for Indonesian languages
Primary Use Cases:
Task-specific instructions, General knowledge instructions
Limitations:
Unsuitable for languages other than English and Indonesian
Considerations:
Perform safety testing and tuning tailored to specific applications of the model before deployment.
Supported Languages 
id (Indonesian), su (Sundanese), jv (Javanese)
Training Details 
Data Sources:
Cendol Collection v1
Methodology:
Instruction-tuned on task-specific NLP data and further tuned on general knowledge from Cendol-Instruct.
Model Architecture:
Decoder-only and encoder-decoder transformer model architectures
Safety Evaluation 
Risk Categories:
Misinformation, Bias
Ethical Considerations:
Testing conducted to date has not covered all scenarios, and the model may in some instances produce inaccurate, biased or other objectionable responses.
Input Output 
Input Format:
Text
Accepted Modalities:
text
Output Format:
Text
LLM NameCendol Llama2 7B Inst
Repository ๐Ÿค—https://huggingface.co/indonlp/cendol-llama2-7b-inst 
Model Size7b
Required VRAM13.5 GB
Updated2025-07-20
Maintainerindonlp
Model Typellama
Model Files  10.0 GB: 1-of-2   3.5 GB: 2-of-2   0.0 GB
Supported Languagesid su jv
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length4096
Model Max Length4096
Transformers Version4.34.0.dev0
Tokenizer ClassLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size32001
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than indonlp/cendol-llama2-7b-inst.

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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 v20241124