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Tinyllama Quant by ElxsiGenwizards

 »  All LLMs  »  ElxsiGenwizards  »  Tinyllama Quant   URL Share it on

  10   
  Arxiv:2309.05463   Autotrain compatible   Code   En   Endpoints compatible   Phi   Region:us
Model Card on HF 🤗: https://huggingface.co/ElxsiGenwizards/tinyllama-quant 

Tinyllama Quant Benchmarks

LLME Score: 0.15443
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Tinyllama Quant (ElxsiGenwizards/tinyllama-quant)
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Tinyllama Quant Parameters and Internals

Model Type 
text generation
Use Cases 
Primary Use Cases:
writing poems, drafting emails, creating stories, summarizing texts, writing Python code
Limitations:
generate inaccurate code and facts, limited scope for code, unreliable responses to instruction, language limitations, potential societal biases, toxicity
Additional Notes 
Phi-1.5 is best suited for prompts using the QA format, the chat format, and the code format. It may produce irrelevant text following the main answer.
Supported Languages 
en (standard)
Training Details 
Data Sources:
same data sources as phi-1, augmented with a new data source that consists of various NLP synthetic texts
Data Volume:
150B tokens
Training Time:
8 days
Hardware Used:
32xA100-40G
Model Architecture:
Transformer-based model with next-word prediction objective
LLM NameTinyllama Quant
Repository 🤗https://huggingface.co/ElxsiGenwizards/tinyllama-quant 
Required VRAM0.8 GB
Updated2025-09-23
MaintainerElxsiGenwizards
Model Typephi
Model Files  0.0 GB   0.8 GB   0.8 GB
Supported Languagesen
Model ArchitecturePhiForCausalLM
Licensemit
Context Length2048
Model Max Length2048
Transformers Version4.37.0
Tokenizer ClassCodeGenTokenizer
Vocabulary Size51200
Torch Data Typefloat16

Best Alternatives to Tinyllama Quant

Best Alternatives
Context / RAM
Downloads
Likes
Merlin1.42K / 5.6 GB50
Merlin1.22K / 5.6 GB50
Phi1.5 Quantized 22K /  GB50
Merlin1.52K / 5.6 GB50
Merlin1.32K / 5.6 GB50
Phi1.5 Update 42K /  GB60
Phi 2 Fp82K / 3.3 GB890
Phi 2 Fp82K / 3.3 GB50
Phi 2 Int8 Ov2K / 0 GB240
Phi 2 Ov Quantized2K / 1.9 GB160
Note: green Score (e.g. "73.2") means that the model is better than ElxsiGenwizards/tinyllama-quant.

Rank the Tinyllama Quant 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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