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Tinyllama PY CODER 4bit Lora 4K V4 by Ramikan-BR

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Tinyllama PY CODER 4bit Lora 4K V4 is an open-source language model by Ramikan-BR. Features: 1.1b LLM, VRAM: 0.7GB, Context: 4K, License: apache-2.0, Quantized, Code Generating, LLM Explorer Score: 0.13.

  4bit   Autotrain compatible Base model:quantized:ramikan-b... Base model:ramikan-br/tinyllam...   Codegen   En   Endpoints compatible   Gguf   Llama   Lora   Pytorch   Q4   Quantized   Region:us   Safetensors   Sft   Trl   Unsloth
Model Card on HF 🤗: https://huggingface.co/Ramikan-BR/tinyllama_PY-CODER-4bit-lora_4k-v4 

Tinyllama PY CODER 4bit Lora 4k V4 Benchmarks

LLME Score: 0.12957
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 V4 (Ramikan-BR/tinyllama_PY-CODER-4bit-lora_4k-v4)
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Tinyllama PY CODER 4bit Lora 4K V4 Parameters and Internals

Model Type 
text-generation-inference, transformers, unsloth
Additional Notes 
This model was finetuned from Ramikan-BR/tinyllama_PY-CODER-bnb-4bit-lora_4k-q4_k_m-v3.
Training Details 
Methodology:
Trained 2x faster with Unsloth and Huggingface's TRL library
LLM NameTinyllama PY CODER 4bit Lora 4k V4
Repository 🤗https://huggingface.co/Ramikan-BR/tinyllama_PY-CODER-4bit-lora_4k-v4 
Base Model(s)  Ramikan-BR/tinyllama_PY-CODER-bnb-4bit-lora_4k-q4_k_m-v3   Ramikan-BR/tinyllama_PY-CODER-bnb-4bit-lora_4k-q4_k_m-v3
Model Size1.1b
Required VRAM0.7 GB
Updated2025-10-01
MaintainerRamikan-BR
Model Typellama
Model Files  2.2 GB   2.2 GB   0.7 GB
Supported Languagesen
GGUF QuantizationYes
Quantization Typegguf|q4|4bit
Generates CodeYes
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length4096
Model Max Length4096
Transformers Version4.40.1
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size32000
LoRA ModelYes
Torch Data Typefloat16

Quantized Models of the Tinyllama PY CODER 4bit Lora 4K V4

Model
Likes
Downloads
VRAM
...llama PY CODER 4bit Lora 4k V50510 GB

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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-v4.

Rank the Tinyllama PY CODER 4bit Lora 4K V4 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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