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Llama 65B Hf by Enoch

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  Autotrain compatible   Endpoints compatible   Llama   Pytorch   Region:us   Sharded
Model Card on HF 🤗: https://huggingface.co/Enoch/llama-65b-hf 

Llama 65B Hf Benchmarks

ARC: 63.31 vs 96.7 (so35)-34.5%
HellaSwag: 86.09 vs 95.3 (gpt4)-9.7%
MMLU: 63.84 vs 88.3 (so35)-27.7%
TruthfulQA: 43.43 vs 59 (gpt4)-26.4%
WinoGrande: 82.48 vs 87.5 (gpt4)-5.7%
GSM8K: 44.81 vs 96.4 (so35)-53.5%
LLME Score: 0.10353
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Llama 65B Hf (Enoch/llama-65b-hf)
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Llama 65B Hf Parameters and Internals

Model Type 
auto-regressive, transformer architecture
Use Cases 
Primary Use Cases:
Research on large language models, Exploring applications such as question answering and reading comprehension, Evaluating and mitigating biases, Determining capabilities and limitations of models
Limitations:
Base model not suitable for downstream applications without risk evaluation
Supported Languages 
en (High proficiency), others (Included 20 languages, mainly supports English)
Training Details 
Data Sources:
CCNet, C4, GitHub, Wikipedia, Books, ArXiv, Stack Exchange
Data Volume:
1T tokens with different breakdowns for different model sizes
Model Architecture:
transformer architecture
Responsible Ai Considerations 
Fairness:
Model reflects biases from web sources. Evaluated biases include gender, religion, race, sexual orientation, age, nationality, disability, physical appearance, and socioeconomic status.
Transparency:
Model trained using web-sourced data which may contain biased and harmful content.
Accountability:
Use GitHub repository to raise questions or comments.
Mitigation Strategies:
Filtered data based on proximity to Wikipedia text using a Kneser-Ney language model and fastText linear classifier.
LLM NameLlama 65B Hf
Repository 🤗https://huggingface.co/Enoch/llama-65b-hf 
Model Size65b
Required VRAM72 GB
Updated2025-09-14
MaintainerEnoch
Model Typellama
Model Files  1.6 GB: 1-of-81   1.6 GB: 2-of-81   1.6 GB: 3-of-81   1.6 GB: 4-of-81   1.6 GB: 5-of-81   1.6 GB: 6-of-81   1.6 GB: 7-of-81   1.6 GB: 8-of-81   1.6 GB: 9-of-81   1.6 GB: 10-of-81   1.6 GB: 11-of-81   1.6 GB: 12-of-81   1.6 GB: 13-of-81   1.6 GB: 14-of-81   1.6 GB: 15-of-81   1.6 GB: 16-of-81   1.6 GB: 17-of-81   1.6 GB: 18-of-81   1.6 GB: 19-of-81   1.6 GB: 20-of-81   1.6 GB: 21-of-81   1.6 GB: 22-of-81   1.6 GB: 23-of-81   1.6 GB: 24-of-81   1.6 GB: 25-of-81   1.6 GB: 26-of-81   1.6 GB: 27-of-81   1.6 GB: 28-of-81   1.6 GB: 29-of-81   1.6 GB: 30-of-81   1.6 GB: 31-of-81   1.6 GB: 32-of-81   1.6 GB: 33-of-81   1.6 GB: 34-of-81   1.6 GB: 35-of-81   1.6 GB: 36-of-81   1.6 GB: 37-of-81   1.6 GB: 38-of-81   1.6 GB: 39-of-81   1.6 GB: 40-of-81   1.6 GB: 41-of-81   1.6 GB: 42-of-81   1.6 GB: 43-of-81   1.6 GB: 44-of-81   1.6 GB: 45-of-81
Model ArchitectureLLaMAForCausalLM
Licenseother
Transformers Version4.28.0.dev0
Vocabulary Size32000
Torch Data Typefloat16

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Rank the Llama 65B Hf 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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Release v20241124
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