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Tinyllama Coder Py 4bit V8 by Ramikan-BR

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Tinyllama Coder Py 4bit V8 is an open-source language model by Ramikan-BR. Features: 1.1b LLM, VRAM: 0.7GB, License: apache-2.0, Quantized, Code Generating, LLM Explorer Score: 0.13.

  4bit Base model:quantized:unsloth/t... Base model:unsloth/tinyllama-c...   Codegen   Conversational   En   Endpoints compatible   Gguf   Llama   Quantized   Region:us   Safetensors   Sft   Trl   Unsloth
Model Card on HF 🤗: https://huggingface.co/Ramikan-BR/tinyllama-coder-py-4bit-v8 

Tinyllama Coder Py 4bit V8 Benchmarks

LLME Score: 0.13342
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Tinyllama Coder Py 4bit V8 (Ramikan-BR/tinyllama-coder-py-4bit-v8)
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Tinyllama Coder Py 4bit V8 Parameters and Internals

Model Type 
text-generation-inference, transformers
Additional Notes 
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
LLM NameTinyllama Coder Py 4bit V8
Repository 🤗https://huggingface.co/Ramikan-BR/tinyllama-coder-py-4bit-v8 
Base Model(s)  Tinyllama Chat Bnb 4bit   unsloth/tinyllama-chat-bnb-4bit
Model Size1.1b
Required VRAM0.7 GB
Updated2026-05-08
MaintainerRamikan-BR
Model Typellama
Model Files  2.2 GB   2.2 GB   0.7 GB   1.2 GB
Supported Languagesen
GGUF QuantizationYes
Quantization Typegguf|4bit
Generates CodeYes
Model ArchitectureAutoModel
Licenseapache-2.0
Model Max Length4096
Tokenizer ClassLlamaTokenizer
Padding Token<unk>

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Rank the Tinyllama Coder Py 4bit V8 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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