TeenyTinyLlama 460M AWQ by nicholasKluge

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  Arxiv:2401.16640   4-bit   Autotrain compatible   Awq Base model:nicholaskluge/teeny... Base model:quantized:nicholask...   Co2 eq emissions Dataset:nicholaskluge/pt-corpu...   Endpoints compatible   Instruct   Llama   Pt   Quantized   Region:us   Safetensors

TeenyTinyLlama 460M AWQ Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
TeenyTinyLlama 460M AWQ (nicholasKluge/TeenyTinyLlama-460m-awq)

TeenyTinyLlama 460M AWQ Parameters and Internals

Model Type 
Transformer-based, Text-generation
Use Cases 
Areas:
Research
Primary Use Cases:
Research challenges related to developing language models for low-resource languages
Limitations:
Not intended for deployment, Not suitable for translation or generating text in other languages
Additional Notes 
Quantized version using AutoAWQ, making it 80% lighter, 20% faster with minimal performance loss.
Supported Languages 
Portuguese (only)
Training Details 
Data Sources:
Pt-Corpus Instruct (6.2B tokens)
Data Volume:
6.2B tokens
Methodology:
Causal language modeling
Context Length:
2048
Training Time:
~ 280 hours
Hardware Used:
1 NVIDIA A100-SXM4-40GB
Model Architecture:
Transformer-based
Input Output 
Accepted Modalities:
Text
Output Format:
Text generation
Performance Tips:
Using quantized models required the installation of `autoawq==0.1.7`. A GPU is required to run the AWQ-quantized models.
LLM NameTeenyTinyLlama 460M AWQ
Repository ๐Ÿค—https://huggingface.co/nicholasKluge/TeenyTinyLlama-460m-awq 
Base Model(s)  TeenyTinyLlama 460M   nicholasKluge/TeenyTinyLlama-460m
Model Size460m
Required VRAM0.3 GB
Updated2024-12-22
MaintainernicholasKluge
Model Typellama
Instruction-BasedYes
Model Files  0.3 GB
Supported Languagespt
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length2048
Model Max Length2048
Transformers Version4.35.2
Tokenizer ClassLlamaTokenizer
Padding Token<pad>
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than nicholasKluge/TeenyTinyLlama-460m-awq.

Rank the TeenyTinyLlama 460M 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241217