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Phi2 Lora Distilabel Intel Orca DPO Pairs by argilla

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  Adapter   Argilla Base model:adapter:microsoft/p...   Base model:microsoft/phi-2 Dataset:argilla/distilabel-int...   Distilabel   Dpo   En   Finetuned   Generated from trainer   Lora   Peft   Region:us   Safetensors   Tensorboard   Trl
Model Card on HF 🤗: https://huggingface.co/argilla/phi2-lora-distilabel-intel-orca-dpo-pairs 

Phi2 Lora Distilabel Intel Orca DPO Pairs Benchmarks

LLME Score: 0.13718
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Phi2 Lora Distilabel Intel Orca DPO Pairs (argilla/phi2-lora-distilabel-intel-orca-dpo-pairs)
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Phi2 Lora Distilabel Intel Orca DPO Pairs Parameters and Internals

Model Type 
text-generation
Use Cases 
Primary Use Cases:
LoRa adapter fine-tine for phi-2
Limitations:
Not a full fine-tune of the model, Did not update parameters extensively
Additional Notes 
The model leverages PeftModel with AutoModelForCausalLM to integrate the LoRa adapter and BitsAndBytes configuration.
Training Details 
Data Sources:
distilabel-intel-orca-dpo-pairs
Methodology:
Fine-tuning using LoRa approach on Google Colab A100 GPU using DPO.
Hardware Used:
Google Colab A100 GPU
Input Output 
Input Format:
Instruction/Output prompt for text generation
Accepted Modalities:
text
Output Format:
Generated text output responding to provided instruction
Performance Tips:
Suitable for LoRa tuning, utilizes bits_n_bytes for optimization.
LLM NamePhi2 Lora Distilabel Intel Orca DPO Pairs
Repository 🤗https://huggingface.co/argilla/phi2-lora-distilabel-intel-orca-dpo-pairs 
Base Model(s)  Phi 2   microsoft/phi-2
Required VRAM0.2 GB
Updated2025-08-20
Maintainerargilla
Model Files  0.2 GB   0.0 GB
Supported Languagesen
Model ArchitectureAdapter
Licensemit
Model Max Length2048
Is Biasednone
Tokenizer ClassCodeGenTokenizer
Padding Token<|endoftext|>
PEFT TypeLORA
LoRA ModelYes
PEFT Target Modulesv_proj|fc1|k_proj|q_proj|fc2
LoRA Alpha16
LoRA Dropout0.5
R Param32

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Note: green Score (e.g. "73.2") means that the model is better than argilla/phi2-lora-distilabel-intel-orca-dpo-pairs.

Rank the Phi2 Lora Distilabel Intel Orca DPO Pairs 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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Release v20241124
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