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Yi 34B 200K Rawrr1 LORA DPO Experimental R2 by adamo1139

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Yi 34B 200K Rawrr1 LORA DPO Experimental R2 is an open-source language model by adamo1139. Features: 34b LLM, VRAM: 0.1GB, LLM Explorer Score: 0.11.

  4-bit   Adapter   Bitsandbytes   Finetuned   Generated from trainer   Llama   Lora   Peft   Region:us
Model Card on HF 🤗: https://huggingface.co/adamo1139/Yi-34B-200K-rawrr1-LORA-DPO-experimental-r2 

Yi 34B 200K Rawrr1 LORA DPO Experimental R2 Benchmarks

LLME Score: 0.11287
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Yi 34B 200K Rawrr1 LORA DPO Experimental R2 (adamo1139/Yi-34B-200K-rawrr1-LORA-DPO-experimental-r2)
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Yi 34B 200K Rawrr1 LORA DPO Experimental R2 Parameters and Internals

Model Type 
LlamaForCausalLM
Use Cases 
Areas:
Research, Commercial applications
Primary Use Cases:
Instruct training, Generating itineraries
Limitations:
Sequence length limitation of 200 tokens
Additional Notes 
Model is designed to run efficient fine-tuning with reduced VRAM requirements using quantization techniques like 'bitsandbytes'.
Training Details 
Data Sources:
/run/media/.../axolotl/datasets/rawrr_v1/
Methodology:
Trained via DPO technique
Context Length:
200
Hardware Used:
RTX 3090 Ti
Model Architecture:
Llama
LLM NameYi 34B 200K Rawrr1 LORA DPO Experimental R2
Repository 🤗https://huggingface.co/adamo1139/Yi-34B-200K-rawrr1-LORA-DPO-experimental-r2 
Model Size34b
Required VRAM0.1 GB
Updated2025-09-23
Maintaineradamo1139
Model Files  0.1 GB
Model ArchitectureAdapter
Model Max Length200000
Is Biasednone
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
PEFT TypeLORA
LoRA ModelYes
PEFT Target Modulesk_proj|down_proj|up_proj|v_proj|q_proj|gate_proj|o_proj
LoRA Alpha8
LoRA Dropout0.05
R Param4

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Note: green Score (e.g. "73.2") means that the model is better than adamo1139/Yi-34B-200K-rawrr1-LORA-DPO-experimental-r2.

Rank the Yi 34B 200K Rawrr1 LORA DPO Experimental R2 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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