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TinyLlama 1.1B 32K GGUF by andrijdavid

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TinyLlama 1.1B 32K GGUF is an open-source language model by andrijdavid. Features: 1.1b LLM, VRAM: 0.5GB, Context: 32K, License: apache-2.0, Quantized, LLM Explorer Score: 0.11.

Dataset:togethercomputer/redpa...   En   Endpoints compatible   Gguf   Llama   Llama 2   Q2   Quantized   Region:us
Model Card on HF 🤗: https://huggingface.co/andrijdavid/TinyLlama-1.1B-32k-GGUF 

TinyLlama 1.1B 32K GGUF Benchmarks

LLME Score: 0.11066
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
TinyLlama 1.1B 32K GGUF (andrijdavid/TinyLlama-1.1B-32k-GGUF)
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TinyLlama 1.1B 32K GGUF Parameters and Internals

Model Type 
text generation
Additional Notes 
Quantization in GGUF format allows various file sizes useful for different computational capacities.
Training Details 
Data Sources:
togethercomputer/RedPajama-Data-1T-Sample
Methodology:
32k context finetune with increased rope theta
Context Length:
32768
LLM NameTinyLlama 1.1B 32K GGUF
Repository 🤗https://huggingface.co/andrijdavid/TinyLlama-1.1B-32k-GGUF 
Base Model(s)  Doctor-Shotgun/TinyLlama-1.1B-32k   Doctor-Shotgun/TinyLlama-1.1B-32k
Model Size1.1b
Required VRAM0.5 GB
Updated2026-05-10
Maintainerandrijdavid
Model Typellama
Model Files  0.5 GB   0.6 GB   0.6 GB   0.6 GB   0.5 GB   0.6 GB   0.7 GB   0.7 GB   0.7 GB   0.6 GB   0.8 GB   0.8 GB   0.8 GB   0.8 GB   0.8 GB   0.9 GB   1.2 GB   2.2 GB
Supported Languagesen
GGUF QuantizationYes
Quantization Typegguf|q2|q4_k|q5_k
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than andrijdavid/TinyLlama-1.1B-32k-GGUF.

Rank the TinyLlama 1.1B 32K GGUF 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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