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Yi 34B 200K HESOYAM 0905 by adamo1139

 »  All LLMs  »  adamo1139  »  Yi 34B 200K HESOYAM 0905   URL Share it on

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  Arxiv:2403.03507   Arxiv:2403.07691   Autotrain compatible   Dataset:adamo1139/hesoyam v0.2 Dataset:adamo1139/rawrr v2-2 s...   Endpoints compatible   Llama   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/adamo1139/Yi-34B-200K-HESOYAM-0905 

Yi 34B 200K HESOYAM 0905 Benchmarks

ARC: 65.61 vs 96.7 (so35)-32.2%
HellaSwag: 83.39 vs 95.3 (gpt4)-12.5%
MMLU: 75.3 vs 88.3 (so35)-14.7%
TruthfulQA: 43.35 vs 59 (gpt4)-26.5%
WinoGrande: 82.95 vs 87.5 (gpt4)-5.2%
GSM8K: 53.68 vs 96.4 (so35)-44.3%
LLME Score: 0.18421
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 HESOYAM 0905 (adamo1139/Yi-34B-200K-HESOYAM-0905)

Yi 34B 200K HESOYAM 0905 Parameters and Internals

Use Cases 
Primary Use Cases:
Text-based sandbox for social media-like interactions
Training Details 
Data Sources:
adamo1139/rawrr_v2-2_stage1, adamo1139/HESOYAM_v0.2
Methodology:
Fine-tuned using ORPO and GaLore methods
Model Architecture:
Second version of 34B 200K model, referred as xlctx
LLM NameYi 34B 200K HESOYAM 0905
Repository 🤗https://huggingface.co/adamo1139/Yi-34B-200K-HESOYAM-0905 
Model Size34b
Required VRAM69.2 GB
Updated2025-05-15
Maintaineradamo1139
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

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Note: green Score (e.g. "73.2") means that the model is better than adamo1139/Yi-34B-200K-HESOYAM-0905.

Rank the Yi 34B 200K HESOYAM 0905 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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