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Yi 6B 200K by 01-ai

 »  All LLMs  »  01-ai  »  Yi 6B 200K   URL Share it on

  7232   
  Arxiv:2311.16502   Arxiv:2401.11944   Arxiv:2403.04652   Autotrain compatible   Endpoints compatible   Llama   Pytorch   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/01-ai/Yi-6B-200K 

Yi 6B 200K Benchmarks

MMLU Pro: 20.49
GPQA: 4.25
MUSR: 16.84
BBH: 20.15
IFEval: 8.43 vs 88 (so35)-90.4%
ARC: 53.58 vs 96.7 (so35)-44.6%
HellaSwag: 75.58 vs 95.3 (gpt4)-20.7%
MMLU: 64.65 vs 88.3 (so35)-26.8%
TruthfulQA: 41.74 vs 59 (gpt4)-29.3%
WinoGrande: 74.27 vs 87.5 (gpt4)-15.1%
GSM8K: 30.33 vs 96.4 (so35)-68.5%
MATH Lvl 5: 1.44
LLME Score: 0.26997
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Yi 6B 200K (01-ai/Yi-6B-200K)

Yi 6B 200K Parameters and Internals

Model Type 
Chat model, Text generation
Use Cases 
Areas:
Chat applications, Creative content generation
Applications:
Commercial applications, Research, Educational tools
Primary Use Cases:
Chatbots, Virtual assistants, Story generation
Limitations:
Potential for hallucination, May produce inconsistent outputs
Considerations:
Adjust generation parameters for desired output qualities.
Additional Notes 
Models do not directly use Llama's weights; unique datasets and training infrastructure emphasize Yi's independent development.
Supported Languages 
English (Fluent), Chinese (Fluent)
Training Details 
Data Sources:
Trainer Multilingual Corpora, 3T Tokens
Data Volume:
3T Multilingual Corpus
Methodology:
Transformer-based architecture
Context Length:
200000
Training Time:
Not specified
Hardware Used:
NVIDIA A800 (80GB), 4090 GPU
Model Architecture:
Based on Llama's architecture
Responsible Ai Considerations 
Fairness:
Addressed during model development.
Transparency:
Standard Transformer architecture; detailed in tech report.
Accountability:
01.AI
Mitigation Strategies:
Use of Supervised Fine-Tuning for better accuracy.
Input Output 
Input Format:
Interactive prompt conversation
Accepted Modalities:
Text
Output Format:
Text responses or follow-ups
Performance Tips:
Calibrate temperature, top_p, top_k settings for desired response diversity.
Release Notes 
Version:
1.0
Date:
2023-11-23
Notes:
Initial open-source release of chat model, supporting both 4-bit and 8-bit quantizations.
Version:
2.0
Date:
2023-12-19
Notes:
Improved performance in coding, math, and reasoning with larger context capabilities.
LLM NameYi 6B 200K
Repository 🤗https://huggingface.co/01-ai/Yi-6B-200K 
Model Size6b
Required VRAM12.1 GB
Updated2024-12-21
Maintainer01-ai
Model Typellama
Model Files  9.9 GB: 1-of-2   2.2 GB: 2-of-2   9.9 GB: 1-of-2   2.2 GB: 2-of-2
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length200000
Model Max Length200000
Transformers Version4.34.0
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size64000
Torch Data Typebfloat16

Quantized Models of the Yi 6B 200K

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VRAM
Yi 6B 200K GGUF0532 GB
Yi 6B 200K GGUF283172 GB
Yi 6B 200K GPTQ2683 GB
Yi 6B 200K AWQ2593 GB

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Rank the Yi 6B 200K 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 v20241217
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