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Sidrap 7B V1 by robinsyihab

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  Autotrain compatible   Code   Conversational   Endpoints compatible   Id   Mistral   Pytorch   Region:us   Sharded
Model Card on HF 🤗: https://huggingface.co/robinsyihab/Sidrap-7B-v1 

Sidrap 7B V1 Benchmarks

LLME Score: 0.13391
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Sidrap 7B V1 (robinsyihab/Sidrap-7B-v1)

Sidrap 7B V1 Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
text generation, dialogue system
Applications:
creating chatbots
Limitations:
may have limitations and biases
Considerations:
Ensure usage is respectful of privacy and aligned with ethical guidelines.
Additional Notes 
The model lacks a moderation mechanism.
Supported Languages 
Bahasa Indonesia (proficient)
Training Details 
Data Sources:
Bahasa Indonesia public dataset
Model Architecture:
Mistral-7B-v0.1 with Grouped-Query Attention, Sliding-Window Attention, Byte-fallback BPE tokenizer
Input Output 
Performance Tips:
Use a system message as the initial input for optimal results.
LLM NameSidrap 7B V1
Repository 🤗https://huggingface.co/robinsyihab/Sidrap-7B-v1 
Model Size7b
Required VRAM15 GB
Updated2025-02-22
Maintainerrobinsyihab
Model Typemistral
Model Files  3.0 GB: 1-of-5   3.0 GB: 2-of-5   2.9 GB: 3-of-5   2.9 GB: 4-of-5   3.2 GB: 5-of-5
Supported Languagesid
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.34.0.dev0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than robinsyihab/Sidrap-7B-v1.

Rank the Sidrap 7B V1 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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