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Tinyllama PY CODER 4bit Lora 4K V12 by Ramikan-BR

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Tinyllama PY CODER 4bit Lora 4K V12 is an open-source language model by Ramikan-BR. Features: 1.1b LLM, VRAM: 2.2GB, Context: 4K, License: apache-2.0, Quantized, Code Generating, LLM Explorer Score: 0.18, Arc: 28.2, HellaSwag: 41.4, MMLU: 26.5.

  4bit Base model:finetune:ramikan-br... Base model:ramikan-br/tinyllam...   Codegen   En   Endpoints compatible   Llama   Lora   Pytorch   Quantized   Region:us   Safetensors   Sft   Trl   Unsloth
Model Card on HF 🤗: https://huggingface.co/Ramikan-BR/tinyllama_PY-CODER-4bit-lora_4k-v12 

Tinyllama PY CODER 4bit Lora 4k V12 Benchmarks

ARC: 28.16 vs 96.7 (so35)-70.9%
HellaSwag: 41.44 vs 95.3 (gpt4)-56.5%
MMLU: 26.49 vs 88.3 (so35)-70%
LLME Score: 0.17691
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Tinyllama PY CODER 4bit Lora 4K V12 (Ramikan-BR/tinyllama_PY-CODER-4bit-lora_4k-v12)
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Tinyllama PY CODER 4bit Lora 4K V12 Parameters and Internals

Model Type 
text generation, inference
Additional Notes 
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
Supported Languages 
en (fluent)
LLM NameTinyllama PY CODER 4bit Lora 4k V12
Repository 🤗https://huggingface.co/Ramikan-BR/tinyllama_PY-CODER-4bit-lora_4k-v12 
Base Model(s)  Ramikan-BR/tinyllama_PY-CODER-4bit-lora_4k-v11   Ramikan-BR/tinyllama_PY-CODER-4bit-lora_4k-v11
Model Size1.1b
Required VRAM2.2 GB
Updated2026-05-25
MaintainerRamikan-BR
Model Typellama
Model Files  2.2 GB   2.2 GB
Supported Languagesen
Quantization Type4bit
Generates CodeYes
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length4096
Model Max Length4096
Transformers Version4.41.0
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size32000
LoRA ModelYes
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than Ramikan-BR/tinyllama_PY-CODER-4bit-lora_4k-v12.

Rank the Tinyllama PY CODER 4bit Lora 4K V12 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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