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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: 68.17-29.2%
HellaSwag: 83.97-11.9%
MMLU: 76.33-11.8%
TruthfulQA: 63.677.9%
WinoGrande: 82.4-5.8%
GSM8K: 72.25-21.5%
nn.n% — How the model compares to the GPT-4.

MM OV Bagel DPO 34B C1000 250 Parameters and Internals

LLM NameMM OV Bagel DPO 34B C1000 250
RepositoryOpen on 🤗 
Model Size34b
Required VRAM69.2 GB
Updated2024-07-27
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)

Best Alternatives to MM OV Bagel DPO 34B C1000 250

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HF Rank
Context/RAM
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Likes
Yi 34B 200K0.3195K / 68.9 GB5280313
Smaug 34B V0.10.3195K / 69.2 GB318558
Yi 34B 200K AEZAKMI V20.3195K / 69.2 GB94812
Smaug 34B V0.1 ExPO0.3195K / 69.2 GB20850
Faro Yi 34B0.3195K / 69.2 GB27486
Bagel DPO 34B V0.50.3195K / 68.7 GB186117
Nous Capybara 34B0.3195K / 68.9 GB6259242
Yi 34B 200K HESOYAM 09050.3195K / 69.2 GB2550
Bagel DPO 34B V0.20.3195K / 69.2 GB276997
Bagel 34B V0.20.3195K / 68.7 GB471338
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 v2024072501
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