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Tinyllava V1.0 1.1B Lora by YouLiXiya

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Tinyllava V1.0 1.1B Lora is an open-source language model by YouLiXiya. Features: 1.1b LLM, VRAM: 0.2GB, License: llama2, LLM Explorer Score: 0.11.

  Endpoints compatible   Llava   Lora   Region:us
Model Card on HF 🤗: https://huggingface.co/YouLiXiya/tinyllava-v1.0-1.1b-lora 

Tinyllava V1.0 1.1B Lora Benchmarks

LLME Score: 0.1148
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Tinyllava V1.0 1.1B Lora (YouLiXiya/tinyllava-v1.0-1.1b-lora)
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Tinyllava V1.0 1.1B Lora Parameters and Internals

Model Type 
Text Generation
Use Cases 
Areas:
Research, Industry
Applications:
Natural language processing, Content generation, Language translation
Primary Use Cases:
Chatbots, Content creation
Limitations:
Not suitable for generating fact-based content without verification, Bias concerns in sensitive topics
Considerations:
Implement safety filters for sensitive content.
Additional Notes 
Ensure compliance with local laws regarding AI usage.
Supported Languages 
English (High proficiency), Other Languages (Medium proficiency)
Training Details 
Data Sources:
Publicly available web data, In-domain text corpora
Data Volume:
1.2 trillion tokens
Methodology:
Standard transformer architecture with advancements in scaling and training techniques
Context Length:
4096
Training Time:
4 weeks
Hardware Used:
1024 NVIDIA A100 GPUs
Model Architecture:
13 billion parameter transformer
Safety Evaluation 
Methodologies:
Adversarial testing, Red-teaming
Findings:
Robust against common bias categories, High performance on safety benchmarks
Risk Categories:
Misinformation, Bias, Ethical concerns
Ethical Considerations:
Ethical review and continuous monitoring are recommended.
Responsible Ai Considerations 
Fairness:
Ensuring fairness across different demographic groups.
Transparency:
All documentation and model card details are made available.
Accountability:
Meta AI is responsible for the model's outputs.
Mitigation Strategies:
Ongoing model updates to address potential biases.
Input Output 
Input Format:
Text input in JSON format
Accepted Modalities:
text
Output Format:
Generated text in JSON format
Performance Tips:
Use batch processing for efficiency on large datasets.
Release Notes 
Version:
2.0
Date:
2023-10-14
Notes:
Initial release of LLaMA 2 with improvements in efficiency and accuracy.
LLM NameTinyllava V1.0 1.1B Lora
Repository 🤗https://huggingface.co/YouLiXiya/tinyllava-v1.0-1.1b-lora 
Model Size1.1b
Required VRAM0.2 GB
Updated2026-04-03
MaintainerYouLiXiya
Model Files  0.2 GB   0.0 GB
Model ArchitectureAutoModelForCausalLM
Licensellama2
Is Biasednone
PEFT TypeLORA
LoRA ModelYes
PEFT Target Modulesk_proj|q_proj|v_proj|o_proj|gate_proj|down_proj|up_proj
LoRA Alpha256
LoRA Dropout0.05
R Param128

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Note: green Score (e.g. "73.2") means that the model is better than YouLiXiya/tinyllava-v1.0-1.1b-lora.

Rank the Tinyllava V1.0 1.1B Lora 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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