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Episodic Lora Merged by kenny2021

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Episodic Lora Merged is an open-source language model by kenny2021. Features: 270m LLM, VRAM: 0.5GB, Context: 32K, License: apache-2.0, Quantized, LLM Explorer Score: 0.26.

  4bit Base model:finetune:unsloth/fu... Base model:unsloth/functiongem...   Conversational   En   Endpoints compatible   Gemma3 text   Lora   Quantized   Region:us   Safetensors   Unsloth
Model Card on HF 🤗: https://huggingface.co/kenny2021/episodic-lora-merged 

Episodic Lora Merged Benchmarks

LLME Score: 0.26235
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Episodic Lora Merged (kenny2021/episodic-lora-merged)
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Episodic Lora Merged Parameters and Internals

LLM NameEpisodic Lora Merged
Repository 🤗https://huggingface.co/kenny2021/episodic-lora-merged 
Model Nameunsloth/functiongemma-270m-it-unsloth-bnb-4bit
Base Model(s)  ...gemma 270M It Unsloth Bnb 4bit   unsloth/functiongemma-270m-it-unsloth-bnb-4bit
Model Size270m
Required VRAM0.5 GB
Updated2026-05-26
Maintainerkenny2021
Model Typegemma3_text
Model Files  0.5 GB
Supported Languagesen
Quantization Type4bit
Model ArchitectureGemma3ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Tokenizer ClassGemmaTokenizer
Padding Token<pad>
Vocabulary Size262144
LoRA ModelYes
Torch Data Typebfloat16

Best Alternatives to Episodic Lora Merged

Best Alternatives
Context / RAM
Downloads
Likes
Episodic Lora Grpo2b Merged32K / 0.5 GB8940
Gemma 3 270M It Qat MLX 4bit32K / 0.2 GB407723
...gemma 270M It Unsloth Bnb 4bit32K / 0.4 GB32472
...mma 3 270M It Unsloth Bnb 4bit32K / 0.4 GB169285
Episodic Lora Grpo2 Merged32K / 0.5 GB660
Raga Radar V232K / 0.9 GB790
Gemma 3 270M It MLX 8bit32K / 0.5 GB44752
Gemma 3 270M It Qat32K / 0.5 GB34263
Gemma 3 270M It 4bit32K / 0.2 GB132110
Gemma 3 270M Unsloth Bnb 4bit32K / 0.4 GB20402
Note: green Score (e.g. "73.2") means that the model is better than kenny2021/episodic-lora-merged.

Rank the Episodic Lora Merged 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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