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Deer 3B by PSanni

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  Autotrain compatible   Bloom   Endpoints compatible   Pytorch   Region:us   Sharded
Model Card on HF 🤗: https://huggingface.co/PSanni/Deer-3b 

Deer 3B Benchmarks

ARC: 38.48 vs 96.7 (so35)-60.2%
HellaSwag: 57.41 vs 95.3 (gpt4)-39.8%
MMLU: 25.64 vs 88.3 (so35)-71%
TruthfulQA: 39.98 vs 59 (gpt4)-32.2%
WinoGrande: 57.46 vs 87.5 (gpt4)-34.3%
GSM8K: 0.3 vs 96.4 (so35)-99.7%
LLME Score: 0.13712
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
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Deer 3B Parameters and Internals

Model Type 
text generation
Additional Notes 
Model isn't attuned to human preferences and could generate unsuitable, unethical, biased, and toxic responses.
Training Details 
Data Volume:
±5k instructions
Methodology:
Fine-tuning
LLM NameDeer 3B
Repository 🤗https://huggingface.co/PSanni/Deer-3b 
Model Size3b
Required VRAM14.6 GB
Updated2025-06-09
MaintainerPSanni
Model Typebloom
Model Files  9.9 GB: 1-of-2   4.7 GB: 2-of-2
Model ArchitectureBloomForCausalLM
Licenseapache-2.0
Transformers Version4.29.2
Tokenizer ClassBloomTokenizer
Padding Token<pad>
Vocabulary Size250683
Torch Data Typefloat32
Deer 3B (PSanni/Deer-3b)

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Blossom V2 3B0K / 6 GB1900
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...lish Dental Raw New Pretrained0K / 3.6 GB140
Note: green Score (e.g. "73.2") means that the model is better than PSanni/Deer-3b.

Rank the Deer 3B 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 v20241124
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