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MM OV Bagel DPO 34B C1000 250 by abacusai

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  Autotrain compatible   Conversational Dataset:abacusai/metamathfewsh...   Endpoints compatible   Llama   Region:us   Safetensors   Sharded   Tensorflow

MM OV Bagel DPO 34B C1000 250 Benchmarks

ARC: 68.17 vs 96.7 (so35)-29.5%
HellaSwag: 83.97 vs 95.3 (gpt4)-11.9%
MMLU: 76.33 vs 88.3 (so35)-13.6%
TruthfulQA: 63.67 vs 59 (gpt4)7.9%
WinoGrande: 82.4 vs 87.5 (gpt4)-5.8%
GSM8K: 72.25 vs 96.4 (so35)-25.1%
LLME Score: 0.198
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

MM OV Bagel DPO 34B C1000 250 Parameters and Internals

LLM NameMM OV Bagel DPO 34B C1000 250
Repository 🤗https://huggingface.co/abacusai/MM-OV-bagel-DPO-34b-c1000-250 
Model Size34b
Required VRAM69.2 GB
Updated2024-09-07
Maintainerabacusai
Model Typellama
Model Files  4.8 GB: 1-of-15   4.8 GB: 2-of-15   5.0 GB: 3-of-15   4.8 GB: 4-of-15   4.8 GB: 5-of-15   5.0 GB: 6-of-15   4.8 GB: 7-of-15   4.8 GB: 8-of-15   5.0 GB: 9-of-15   4.8 GB: 10-of-15   4.8 GB: 11-of-15   5.0 GB: 12-of-15   4.8 GB: 13-of-15   4.8 GB: 14-of-15   1.2 GB: 15-of-15
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length200000
Model Max Length200000
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size64000
Torch Data Typefloat16
MM OV Bagel DPO 34B C1000 250 (abacusai/MM-OV-bagel-DPO-34b-c1000-250)

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Note: green Score (e.g. "73.2") means that the model is better than abacusai/MM-OV-bagel-DPO-34b-c1000-250.

Rank the MM OV Bagel DPO 34B C1000 250 Capabilities

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Instruction Following and Task Automation  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v2024072803
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