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Meta Llama 3 8B Instruct Hf AWQ by solidrust

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  4-bit   Autotrain compatible   Awq Base model:quantized:undi95/me... Base model:undi95/meta-llama-3...   Conversational   Endpoints compatible   Facebook   Instruct   Llama   Llama-3   Meta   Pytorch   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/solidrust/Meta-Llama-3-8B-Instruct-hf-AWQ 

Meta Llama 3 8B Instruct Hf AWQ Benchmarks

ARC: 59.64 vs 96.7 (so35)-38.3%
HellaSwag: 78.84 vs 95.3 (gpt4)-17.3%
MMLU: 65.06 vs 88.3 (so35)-26.3%
TruthfulQA: 50.17 vs 59 (gpt4)-15%
WinoGrande: 74.98 vs 87.5 (gpt4)-14.3%
GSM8K: 57.32 vs 96.4 (so35)-40.5%
LLME Score: 0.21766
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Meta Llama 3 8B Instruct Hf AWQ (solidrust/Meta-Llama-3-8B-Instruct-hf-AWQ)

Meta Llama 3 8B Instruct Hf AWQ Parameters and Internals

Model Type 
text-generation
Use Cases 
Primary Use Cases:
dialogue use cases
Additional Notes 
Llama 3 instruction tuned models are optimized for dialogue use cases and outperform many of the available open-source chat models on common industry benchmarks.
Training Details 
Methodology:
The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety.
Model Architecture:
Llama 3 is an auto-regressive language model that uses an optimized transformer architecture.
Responsible Ai Considerations 
Fairness:
The tuned versions are optimized for human preferences for helpfulness and safety.
Input Output 
Input Format:
Models input text only.
Output Format:
Models generate text and code only.
LLM NameMeta Llama 3 8B Instruct Hf AWQ
Repository 🤗https://huggingface.co/solidrust/Meta-Llama-3-8B-Instruct-hf-AWQ 
Base Model(s)  Meta Llama 3 8B Instruct Hf   Undi95/Meta-Llama-3-8B-Instruct-hf
Model Size8b
Required VRAM5.8 GB
Updated2025-01-21
Maintainersolidrust
Model Typellama
Instruction-BasedYes
Model Files  4.7 GB: 1-of-2   1.1 GB: 2-of-2
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureLlamaForCausalLM
Licenseother
Context Length8192
Model Max Length8192
Transformers Version4.38.2
Tokenizer ClassPreTrainedTokenizerFast
Vocabulary Size128256
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than solidrust/Meta-Llama-3-8B-Instruct-hf-AWQ.

Rank the Meta Llama 3 8B Instruct Hf AWQ 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 v20241227
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