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Fuyu 8B by adept

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  Autotrain compatible   Endpoints compatible   Fuyu   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/adept/fuyu-8b 

Fuyu 8B Benchmarks

LLME Score: 0.23269
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Fuyu 8B (adept/fuyu-8b)

Fuyu 8B Parameters and Internals

Model Type 
Decoder-only, Multi-modal, Transformer
Use Cases 
Areas:
Research
Applications:
Computer control, Digital agents, Research on multi-modal models
Limitations:
Faces and people in general may not be generated properly, The model was not trained to be factual or true representations of people or events
Additional Notes 
The model is optimized for digital agents and responds well to few-shotting and fine-tuning.
Training Details 
Model Architecture:
Vanilla decoder-only transformer without an image encoder, using linear projection of image patches into the transformer.
Input Output 
Input Format:
Text and images (image patches are linearly projected)
Accepted Modalities:
Text, Images
Output Format:
Text
Performance Tips:
End questions with `\n` for best performance.
LLM NameFuyu 8B
Repository 🤗https://huggingface.co/adept/fuyu-8b 
Model Size8b
Required VRAM18.8 GB
Updated2024-10-30
Maintaineradept
Model Typefuyu
Model Files  9.9 GB: 1-of-2   8.9 GB: 2-of-2
Model ArchitectureFuyuForCausalLM
Licensecc-by-nc-4.0
Context Length16384
Model Max Length16384
Transformers Version4.35.0.dev0
Tokenizer ClassLlamaTokenizer
Vocabulary Size262144
Torch Data Typebfloat16

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Fuyu 8B Sharded16K / 18.8 GB1345

Rank the Fuyu 8B 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227
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