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Tinyllama Coder Py 4bit V10 by Ramikan-BR

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Tinyllama Coder Py 4bit V10 is an open-source language model by Ramikan-BR. Features: 1.1b LLM, VRAM: 0.7GB, Context: 4K, License: apache-2.0, Quantized, Instruction-Based, Code Generating, LLM Explorer Score: 0.18, Arc: 34.4, HellaSwag: 56.3, MMLU: 26.4, GSM8K: 0.5.

  4bit Base model:adapter:unsloth/tin... Base model:unsloth/tinyllama-c...   Code   Codegen   Conversational Dataset:ramikan-br/data-oss in...   En   Endpoints compatible   Gguf   Instruct   Llama   Lora   Peft   Quantized   Region:us   Safetensors   Sft   Trl   Unsloth
Model Card on HF 🤗: https://huggingface.co/Ramikan-BR/tinyllama-coder-py-4bit-v10 

Tinyllama Coder Py 4bit V10 Benchmarks

ARC: 34.39 vs 96.7 (so35)-64.4%
HellaSwag: 56.34 vs 95.3 (gpt4)-40.9%
MMLU: 26.42 vs 88.3 (so35)-70.1%
GSM8K: 0.53 vs 96.4 (so35)-99.5%
LLME Score: 0.18022
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 V10 (Ramikan-BR/tinyllama-coder-py-4bit-v10)
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Tinyllama Coder Py 4bit V10 Parameters and Internals

Model Type 
text-generation, Python Coder
Additional Notes 
The model was refined using Unsloath. The dataset ise-uiuc/Magicoder-OSS-Instruct-75K was adjusted, leaving only data on Python and divided into 10 parts, each refinement occurred for 2 epochs, using Adafactor optimizer or AdamW_8bit (Adafactor seems to deliver less loss).
Supported Languages 
en (NLP)
Training Details 
Data Sources:
Ramikan-BR/data-oss_instruct-decontaminated_python.jsonl
Methodology:
The model was refined using Unsloath.
LLM NameTinyllama Coder Py 4bit V10
Repository 🤗https://huggingface.co/Ramikan-BR/tinyllama-coder-py-4bit-v10 
Base Model(s)  Tinyllama Chat Bnb 4bit   unsloth/tinyllama-chat-bnb-4bit
Model Size1.1b
Required VRAM0.7 GB
Updated2026-05-05
MaintainerRamikan-BR
Model Typellama
Instruction-BasedYes
Model Files  2.2 GB   2.2 GB   0.7 GB   1.2 GB
Supported Languagesen
GGUF QuantizationYes
Quantization Typegguf|4bit
Generates CodeYes
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length4096
Model Max Length4096
Transformers Version4.40.2
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size32000
Torch Data Typefloat16

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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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