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Gemma Unsloth Alpaca by gnumanth

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Gemma Unsloth Alpaca is an open-source language model by gnumanth. Features: 7b LLM, VRAM: 17.1GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.13.

  4bit Base model:finetune:unsloth/ge... Base model:unsloth/gemma-7b-bn...   Conversational   En   Endpoints compatible   Gemma   Lora   Quantized   Region:us   Safetensors   Sharded   Tensorflow   Trl   Unsloth
Model Card on HF 🤗: https://huggingface.co/gnumanth/gemma-unsloth-alpaca 

Gemma Unsloth Alpaca Benchmarks

LLME Score: 0.12536
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Gemma Unsloth Alpaca (gnumanth/gemma-unsloth-alpaca)
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Gemma Unsloth Alpaca Parameters and Internals

Model Type 
text generation
Input Output 
Accepted Modalities:
text
LLM NameGemma Unsloth Alpaca
Repository 🤗https://huggingface.co/gnumanth/gemma-unsloth-alpaca 
Base Model(s)  Gemma 7B Bnb 4bit   unsloth/gemma-7b-bnb-4bit
Model Size7b
Required VRAM17.1 GB
Updated2026-04-20
Maintainergnumanth
Model Files  0.2 GB   5.0 GB: 1-of-4   5.0 GB: 2-of-4   5.0 GB: 3-of-4   2.1 GB: 4-of-4
Supported Languagesen
Quantization Type4bit
Model ArchitectureAutoModelForCausalLM
Licenseapache-2.0
Model Max Length8192
Is Biasednone
Tokenizer ClassGemmaTokenizer
Padding Token<pad>
PEFT TypeLORA
LoRA ModelYes
PEFT Target Modulesdown_proj|up_proj|k_proj|q_proj|o_proj|v_proj|gate_proj
LoRA Alpha16
LoRA Dropout0
R Param16

Best Alternatives to Gemma Unsloth Alpaca

Best Alternatives
Context / RAM
Downloads
Likes
Qwen2.5 8K Sports0K / 15.2 GB140
WorldBuilder 7B0K / 14.5 GB61
Unsloth Alpaca0K / 14.5 GB90
... WAEMU Africa Banking Analysis0K / 15.2 GB21
Gemma 7B Bnb 4bit0K / 17.1 GB50
Mistral 7B V0.30K / 14.5 GB60
Mistralbasket10K / 0.2 GB70
Refined Llama30K / 0.2 GB60
Mistral 7B Instruct 4bit0K / 0.2 GB41
Qwen 2 Healthcare Checkpoint 10K / 15.2 GB00
Note: green Score (e.g. "73.2") means that the model is better than gnumanth/gemma-unsloth-alpaca.

Rank the Gemma Unsloth Alpaca 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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