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Tinyllama Coder Py V23 by Ramikan-BR

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  4bit   Autotrain compatible Base model:quantized:unsloth/t... Base model:unsloth/tinyllama-c...   Codegen   Conversational   En   Endpoints compatible   Gguf   Llama   Pytorch   Quantized   Region:us   Safetensors   Sft   Trl   Unsloth
Model Card on HF 🤗: https://huggingface.co/Ramikan-BR/tinyllama-coder-py-v23 

Tinyllama Coder Py V23 Benchmarks

LLME Score: 0.22036
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 V23 (Ramikan-BR/tinyllama-coder-py-v23)

Tinyllama Coder Py V23 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 V23
Repository 🤗https://huggingface.co/Ramikan-BR/tinyllama-coder-py-v23 
Base Model(s)  Tinyllama Chat Bnb 4bit   unsloth/tinyllama-chat-bnb-4bit
Model Size1.1b
Required VRAM2.2 GB
Updated2024-12-21
MaintainerRamikan-BR
Model Typellama
Model Files  2.2 GB   2.2 GB   2.2 GB
Supported Languagesen
GGUF QuantizationYes
Quantization Typegguf|4bit
Generates CodeYes
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length4096
Model Max Length4096
Transformers Version4.41.2
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than Ramikan-BR/tinyllama-coder-py-v23.

Rank the Tinyllama Coder Py V23 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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Release v20241217
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