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Gemma 7B Malayalam T2 Model Vllm 4bit by animaRegem

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Gemma 7B Malayalam T2 Model Vllm 4bit Benchmarks

LLME Score: 0.20836
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 Model Vllm 4bit Parameters and Internals

Model Type 
text generation
Additional Notes 
Uploaded model developed by animaRegem. Finetuned from unsloth/gemma-7b-bnb-4bit
Training Details 
Methodology:
Trained 2x faster with Unsloth and Huggingface's TRL library.
LLM NameGemma 7B Malayalam T2 Model Vllm 4bit
Repository 🤗https://huggingface.co/animaRegem/gemma-7b-malayalam-t2-model-vllm-4bit 
Base Model(s)  Gemma 7B Bnb 4bit   unsloth/gemma-7b-bnb-4bit
Model Size7b
Required VRAM5.6 GB
Updated2024-11-21
MaintaineranimaRegem
Model Typegemma
Model Files  5.0 GB: 1-of-2   0.6 GB: 2-of-2
Supported Languagesen
Quantization Type4bit
Model ArchitectureGemmaForCausalLM
Licenseapache-2.0
Context Length8192
Model Max Length8192
Transformers Version4.41.1
Tokenizer ClassGemmaTokenizer
Padding Token<pad>
Vocabulary Size256000
Torch Data Typefloat16
Gemma 7B Malayalam T2 Model Vllm 4bit (animaRegem/gemma-7b-malayalam-t2-model-vllm-4bit)

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Context / RAM
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...t Cleaner Gemma 32k Merged 16b31K / 17.1 GB180
...ruct Malayalam Model Vllm 4bit16K / 5.6 GB220
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Fbt Gemma 7B8K / 17.1 GB50
Codegemma 7B 4bit8K / 5.9 GB280
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Codegemma 7B It 4bit8K / 5.9 GB121
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Gemma 1.1 7B It 4bit8K / 5.9 GB124
Note: green Score (e.g. "73.2") means that the model is better than animaRegem/gemma-7b-malayalam-t2-model-vllm-4bit.

Rank the Gemma 7B Malayalam T2 Model Vllm 4bit 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 v20241110
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