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Faro Yi 34B by wenbopan

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Faro Yi 34B is an open-source language model by wenbopan. Features: 34b LLM, VRAM: 69.2GB, Context: 195K, License: mit, Merged, LLM Explorer Score: 0.16, Arc: 66.6, HellaSwag: 83.5, MMLU: 76.6, GSM8K: 65.3.

  Merged Model   Arxiv:2303.08774   Conversational   Dataset:wenbopan/fusang-v1 Dataset:wenbopan/openorca-zh-2...   En   Endpoints compatible   Llama   Region:us   Safetensors   Sharded   Tensorflow   Zh
Model Card on HF 🤗: https://huggingface.co/wenbopan/Faro-Yi-34B 

Faro Yi 34B Benchmarks

ARC: 66.55 vs 96.7 (so35)-31.2%
HellaSwag: 83.53 vs 95.3 (gpt4)-12.4%
MMLU: 76.6 vs 88.3 (so35)-13.3%
GSM8K: 65.28 vs 96.4 (so35)-32.3%
LLME Score: 0.16436
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Faro Yi 34B (wenbopan/Faro-Yi-34B)
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Faro Yi 34B Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
various downstream tasks
Supported Languages 
zh (full proficiency), en (full proficiency)
Training Details 
Data Sources:
Fusang-V1, OpenOrca-zh-20k
Methodology:
Instruction tuning with large-scale synthetic data.
Context Length:
200000
Input Output 
Input Format:
ChatML template for messages.
Accepted Modalities:
text
Output Format:
Generated text based on given input and instructions.
Performance Tips:
Use vLLM for long inputs.
LLM NameFaro Yi 34B
Repository 🤗https://huggingface.co/wenbopan/Faro-Yi-34B 
Merged ModelYes
Model Size34b
Required VRAM69.2 GB
Updated2026-05-29
Maintainerwenbopan
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
Supported Languageszh en
Model ArchitectureLlamaForCausalLM
Licensemit
Context Length200000
Model Max Length200000
Transformers Version4.39.0.dev0
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size64000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than wenbopan/Faro-Yi-34B.

Rank the Faro Yi 34B 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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