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Agri Wala Llama3 by parthrautV

 »  All LLMs  »  parthrautV  »  Agri Wala Llama3   URL Share it on

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  Dataset:parthrautv/agri llama3   Endpoints compatible   Gguf   Llama   Quantized   Region:us
Model Card on HF 🤗: https://huggingface.co/parthrautV/agri_wala_llama3 

Agri Wala Llama3 Benchmarks

LLME Score: 0.18601
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Agri Wala Llama3 (parthrautV/agri_wala_llama3)

Agri Wala Llama3 Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
Agriculture Research
Applications:
Crop yield prediction, Soil health analysis
Primary Use Cases:
Research on agricultural data enhancements
Limitations:
Not suitable for non-agricultural data
Considerations:
Ensure data relevance to agriculture
Additional Notes 
Optimum performance when used in agricultural settings
Training Details 
Data Sources:
Parth Raut's Dataset
Data Volume:
500 million tokens
Methodology:
Fine-tuning based on LLaMA
Context Length:
2048
Training Time:
72 hours
Hardware Used:
4 A100 GPUs
Model Architecture:
Transformer-based architecture
Responsible Ai Considerations 
Transparency:
Model's performance is detailed publicly
Accountability:
Developer responsible for intended use guidance
Input Output 
Input Format:
JSON input with agricultural data
Accepted Modalities:
text
Output Format:
JSON output with predictions and insights
Performance Tips:
Ensure input data quality for better predictions.
Release Notes 
Version:
v1.0
Date:
2023-09-15
Notes:
Initial release with fine-tuned improvements.
LLM NameAgri Wala Llama3
Repository 🤗https://huggingface.co/parthrautV/agri_wala_llama3 
Required VRAM16.1 GB
Updated2025-02-22
MaintainerparthrautV
Model Typellama
Model Files  16.1 GB
GGUF QuantizationYes
Quantization Typegguf
Model ArchitectureAutoModel

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Note: green Score (e.g. "73.2") means that the model is better than parthrautV/agri_wala_llama3.

Rank the Agri Wala Llama3 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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