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Bumblebee Light by MonolithFoundation

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  Autotrain compatible   Conversational   Endpoints compatible   Llava llama   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/MonolithFoundation/Bumblebee-Light 

Bumblebee Light Benchmarks

LLME Score: 0.1828
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Bumblebee Light (MonolithFoundation/Bumblebee-Light)

Bumblebee Light Parameters and Internals

Model Type 
VLM, MLLM, Multi-Modal LLM
Use Cases 
Areas:
Research, Commercial applications
Applications:
Chinese OCR understanding, Reasoning, Table and Graphic comprehension, Math calculation
Additional Notes 
Bumblebee is open-source and its weights are available for research purposes to aid the democratization of multi-modal open-source community.
Supported Languages 
zh (Superior performance)
Training Details 
Data Sources:
HuggingFaceFW/fineweb, YanweiLi/MGM-Instruction
Context Length:
576
Model Architecture:
14B LLM-driven multi-modal model, similar to LLaVA architecture with MGM's dual tower visual information input
Input Output 
Accepted Modalities:
text, visual
Release Notes 
Version:
2024.04.25
Date:
2024-04-25
Notes:
First version of Bumblebee released.
LLM NameBumblebee Light
Repository 🤗https://huggingface.co/MonolithFoundation/Bumblebee-Light 
Model Size7b
Required VRAM18.6 GB
Updated2025-02-22
MaintainerMonolithFoundation
Model Typellava_llama
Model Files  5.0 GB: 1-of-4   5.0 GB: 2-of-4   5.0 GB: 3-of-4   3.6 GB: 4-of-4
Model ArchitectureLlavaQwen2ForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.39.3
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151646
Torch Data Typefloat16
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than MonolithFoundation/Bumblebee-Light.

Rank the Bumblebee Light Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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