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BabyMistral by OEvortex

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  Autotrain compatible   Conversational   En   Endpoints compatible   Gguf   Mistral   Q4   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/OEvortex/BabyMistral 

BabyMistral Benchmarks

LLME Score: 0.22377
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
BabyMistral (OEvortex/BabyMistral)

BabyMistral Parameters and Internals

Model Type 
text-generation
Use Cases 
Applications:
Text completion and generation, Creative writing assistance, Dialogue systems, Question answering, Language understanding tasks
Limitations:
May struggle with very specialized or technical domains, Lacks real-time knowledge beyond its training data, Potential for generating plausible-sounding but incorrect information
Supported Languages 
en (proficient)
Training Details 
Data Sources:
1.5 trillion tokens
Data Volume:
1.5 trillion tokens
Methodology:
Trained from scratch
Training Time:
70 days
Hardware Used:
4x NVIDIA A100 GPUs
Model Architecture:
Based on Mistral
Responsible Ai Considerations 
Fairness:
The model may reproduce biases present in its training data.
Mitigation Strategies:
Generated content should be reviewed for accuracy and appropriateness.
LLM NameBabyMistral
Repository 🤗https://huggingface.co/OEvortex/BabyMistral 
Model Size1.6b
Required VRAM0.9 GB
Updated2025-01-22
MaintainerOEvortex
Model Typemistral
Model Files  0.9 GB   3.1 GB
Supported Languagesen
GGUF QuantizationYes
Quantization Typeq4|gguf|q4_k
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length8192
Model Max Length8192
Transformers Version4.44.0
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size32002
Torch Data Typebfloat16

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