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Vi Gemma 2B RAG by ricepaper

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  4bit   Autotrain compatible Base model:finetune:unsloth/ge... Base model:unsloth/gemma-1.1-2...   Conversational   En   Endpoints compatible   Gemma   Pytorch   Quantized   Region:us   Retrieval-augmented-generation   Safetensors   Sft   Sharded   Tensorflow   Trl   Unsloth   Vi
Model Card on HF 🤗: https://huggingface.co/ricepaper/vi-gemma-2b-RAG 

Vi Gemma 2B RAG Benchmarks

LLME Score: 0.24457
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Vi Gemma 2B RAG (ricepaper/vi-gemma-2b-RAG)

Vi Gemma 2B RAG Parameters and Internals

LLM NameVi Gemma 2B RAG
Repository 🤗https://huggingface.co/ricepaper/vi-gemma-2b-RAG 
Base Model(s)  unsloth/gemma-1.1-2b-it-bnb-4bit   unsloth/gemma-1.1-2b-it-bnb-4bit
Model Size2b
Required VRAM5.1 GB
Updated2024-12-22
Maintainerricepaper
Model Typegemma
Model Files  5.0 GB: 1-of-2   0.1 GB: 2-of-2   5.0 GB: 1-of-2   0.1 GB: 2-of-2
Supported Languagesen vi
Quantization Type4bit
Model ArchitectureGemmaForCausalLM
Licenseapache-2.0
Context Length8192
Model Max Length8192
Transformers Version4.43.3
Tokenizer ClassGemmaTokenizer
Padding Token<pad>
Vocabulary Size256000
Torch Data Typefloat16

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Rank the Vi Gemma 2B RAG Capabilities

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Release v20241217
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