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Gemma 7B Malayalam T2 Gguf by animaRegem

 »  All LLMs  »  animaRegem  »  Gemma 7B Malayalam T2 Gguf   URL Share it on

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  4bit Base model:quantized:unsloth/g... Base model:unsloth/gemma-7b-bn...   En   Endpoints compatible   Gemma   Gguf   Quantized   Region:us   Unsloth
Model Card on HF 🤗: https://huggingface.co/animaRegem/gemma-7b-malayalam-t2-gguf 

Gemma 7B Malayalam T2 Gguf Benchmarks

LLME Score: 0.18988
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Gemma 7B Malayalam T2 Gguf (animaRegem/gemma-7b-malayalam-t2-gguf)

Gemma 7B Malayalam T2 Gguf Parameters and Internals

Model Type 
text-generation-inference, transformers, unsloth, gemma, gguf
Additional Notes 
This gemma model was trained 2x faster with Unsloth and Huggingface's TRL library.
Training Details 
Training Time:
2x faster
LLM NameGemma 7B Malayalam T2 Gguf
Repository 🤗https://huggingface.co/animaRegem/gemma-7b-malayalam-t2-gguf 
Base Model(s)  Gemma 7B Bnb 4bit   unsloth/gemma-7b-bnb-4bit
Model Size7b
Required VRAM5.3 GB
Updated2025-02-22
MaintaineranimaRegem
Model Typegemma
Model Files  5.3 GB
Supported Languagesen
GGUF QuantizationYes
Quantization Typegguf|4bit
Model ArchitectureAutoModel
Licenseapache-2.0

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Note: green Score (e.g. "73.2") means that the model is better than animaRegem/gemma-7b-malayalam-t2-gguf.

Rank the Gemma 7B Malayalam T2 Gguf 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227
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