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Mit B0 Image Segmentation Carvana Image Masking by DunnBC22

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Mit B0 Image Segmentation Carvana Image Masking is an open-source language model by DunnBC22. Features: LLM, License: other, LLM Explorer Score: 0.09.

  Adapter   En   Finetuned   Generated from trainer   Image-segmentation   Image masking   Lora   Pytorch   Region:us   Tensorboard
Model Card on HF 🤗: https://huggingface.co/DunnBC22/mit-b0-Image_segmentation-Carvana_Image_Masking 

Mit B0 Image Segmentation Carvana Image Masking Benchmarks

LLME Score: 0.08646
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mit B0 Image Segmentation Carvana Image Masking (DunnBC22/mit-b0-Image_segmentation-Carvana_Image_Masking)
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Mit B0 Image Segmentation Carvana Image Masking Parameters and Internals

Model Type 
image-segmentation
Use Cases 
Primary Use Cases:
Image Segmentation
Considerations:
Ensure proper citation of authors for datasets and technologies used.
Additional Notes 
Used for skillset improvement. Training hyperparameters include a learning rate of 0.0005, train and eval batch size of 8, and an Adam optimizer.
Supported Languages 
en (High proficiency)
Training Details 
Data Sources:
https://www.kaggle.com/datasets/ipythonx/carvana-image-masking-png
Methodology:
fine-tuning
Model Architecture:
Using a fine-tuned version of nvidia/mit-b0 for image segmentation
LLM NameMit B0 Image Segmentation Carvana Image Masking
Repository 🤗https://huggingface.co/DunnBC22/mit-b0-Image_segmentation-Carvana_Image_Masking 
Required VRAM0 GB
Updated2026-04-07
MaintainerDunnBC22
Model Files  0.0 GB   0.0 GB   0.0 GB
Supported Languagesen
Model ArchitectureAdapter
Licenseother
Is Biasedlora_only
PEFT TypeLORA
LoRA ModelYes
PEFT Target Modulesquery|values
LoRA Alpha32
LoRA Dropout0.1
R Param32

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Note: green Score (e.g. "73.2") means that the model is better than DunnBC22/mit-b0-Image_segmentation-Carvana_Image_Masking.

Rank the Mit B0 Image Segmentation Carvana Image Masking 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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