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Limarpv3 Yi Llama 34B Lora by Doctor-Shotgun

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Limarpv3 Yi Llama 34B Lora is an open-source language model by Doctor-Shotgun. Features: 34b LLM, VRAM: 1GB, License: apache-2.0, LLM Explorer Score: 0.1.

  8-bit   Autotrain compatible   Bitsandbytes   Dataset:lemonilia/limarp   Generated from trainer   Llama   Lora   Region:us   Yi
Model Card on HF 🤗: https://huggingface.co/Doctor-Shotgun/limarpv3-yi-llama-34b-lora 

Limarpv3 Yi Llama 34B Lora Benchmarks

LLME Score: 0.10423
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Limarpv3 Yi Llama 34B Lora (Doctor-Shotgun/limarpv3-yi-llama-34b-lora)
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Limarpv3 Yi Llama 34B Lora Parameters and Internals

Model Type 
longform-oriented, novel-style roleplaying chat
Use Cases 
Areas:
roleplaying forums
Primary Use Cases:
novel-style roleplaying chats
Limitations:
may not support short-form IRC/Discord-style RP
Considerations:
intended for replicating 1-on-1 roleplay experience
Additional Notes 
The model does not include instruction tuning, only manually picked and slightly edited RP conversations with persona and scenario data.
Training Details 
Data Sources:
lemonilia/LimaRP
Model Architecture:
similar to a Llama 2 34B model with an expanded vocab size of 64000
Input Output 
Input Format:
extended Alpaca format
LLM NameLimarpv3 Yi Llama 34B Lora
Repository 🤗https://huggingface.co/Doctor-Shotgun/limarpv3-yi-llama-34b-lora 
Model Size34b
Required VRAM1 GB
Updated2025-09-23
MaintainerDoctor-Shotgun
Model Files  1.0 GB
Model ArchitectureAutoModelForCausalLM
Licenseapache-2.0
Model Max Length4096
Is Biasednone
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
PEFT TypeLORA
LoRA ModelYes
PEFT Target Moduleso_proj|q_proj|v_proj|down_proj|up_proj|gate_proj|k_proj
LoRA Alpha16
LoRA Dropout0.05
R Param32

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Yi 34B GiftedConvo0K / 5.8 GB22
Note: green Score (e.g. "73.2") means that the model is better than Doctor-Shotgun/limarpv3-yi-llama-34b-lora.

Rank the Limarpv3 Yi Llama 34B Lora 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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