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Bagel DPO 7B V0.1 by jondurbin

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  Autotrain compatible   Conversational   Dataset:ai2 arc Dataset:allenai/ultrafeedback ...   Dataset:boolq   Dataset:cais/mmlu   Dataset:cakiki/rosetta-code   Dataset:codeparrot/apps   Dataset:datasets/winogrande   Dataset:drop   Dataset:facebook/belebele   Dataset:intel/orca dpo pairs Dataset:jondurbin/cinematika-v... Dataset:jondurbin/truthy-dpo-v...   Dataset:lmsys/lmsys-chat-1m Dataset:migtissera/synthia-v1.... Dataset:muennighoff/natural-in...   Dataset:nvidia/helpsteer   Dataset:open-orca/slimorca   Dataset:openbookqa   Dataset:piqa   Dataset:spider   Dataset:squad v2   Dataset:tiger-lab/mathinstruct   Dataset:unalignment/spicy-3.1 Dataset:unalignment/toxic-dpo-... Dataset:vezora/tested-22k-pyth...   Endpoints compatible   Llama   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/jondurbin/bagel-dpo-7b-v0.1 

Bagel DPO 7B V0.1 Benchmarks

ARC: 66.72 vs 96.7 (so35)-31%
HellaSwag: 84.16 vs 95.3 (gpt4)-11.7%
MMLU: 64.24 vs 88.3 (so35)-27.2%
TruthfulQA: 64.05 vs 59 (gpt4)8.6%
WinoGrande: 80.9 vs 87.5 (gpt4)-7.5%
GSM8K: 47.61 vs 96.4 (so35)-50.6%
LLME Score: 0.18677
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Bagel DPO 7B V0.1 (jondurbin/bagel-dpo-7b-v0.1)

Bagel DPO 7B V0.1 Parameters and Internals

Model Type 
text generation, instruction following
Additional Notes 
The model uses a mix of prompt formats including Vicuna, Llama-2, Alpaca, and Chat-ML (sort of).
Training Details 
Data Sources:
ai2_arc, unalignment/spicy-3.1, codeparrot/apps, facebook/belebele, boolq, jondurbin/cinematika-v0.1, drop, lmsys/lmsys-chat-1m, TIGER-Lab/MathInstruct, cais/mmlu, Muennighoff/natural-instructions, openbookqa, piqa, Vezora/Tested-22k-Python-Alpaca, cakiki/rosetta-code, Open-Orca/SlimOrca, spider, squad_v2, migtissera/Synthia-v1.3, datasets/winogrande, nvidia/HelpSteer, Intel/orca_dpo_pairs, unalignment/toxic-dpo-v0.1, jondurbin/truthy-dpo-v0.1, allenai/ultrafeedback_binarized_cleaned
Data Volume:
1,671,822 items
Methodology:
Supervised Fine-tuning (SFT) and Direct Preference Optimization (DPO)
Input Output 
Input Format:
Accepted Modalities:
text
Output Format:
text
LLM NameBagel DPO 7B V0.1
Repository 🤗https://huggingface.co/jondurbin/bagel-dpo-7b-v0.1 
Model Size7b
Required VRAM14.4 GB
Updated2025-03-14
Maintainerjondurbin
Model Typellama
Model Files  4.9 GB: 1-of-3   5.0 GB: 2-of-3   4.5 GB: 3-of-3
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size32000
Torch Data Typebfloat16

Quantized Models of the Bagel DPO 7B V0.1

Model
Likes
Downloads
VRAM
Bagel DPO 7B V0.1 GGUF52823 GB
Bagel DPO 7B V0.1 AWQ0884 GB
Bagel DPO 7B V0.1 GPTQ0424 GB

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Note: green Score (e.g. "73.2") means that the model is better than jondurbin/bagel-dpo-7b-v0.1.

Rank the Bagel DPO 7B V0.1 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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Release v20241227
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