Yi 6B 200K AEZAKMI V2 by adamo1139

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  Autotrain compatible   Endpoints compatible   Llama   Region:us   Safetensors   Sharded   Tensorflow

Yi 6B 200K AEZAKMI V2 Benchmarks

Yi 6B 200K AEZAKMI V2 (adamo1139/Yi-6B-200K-AEZAKMI-v2)

Yi 6B 200K AEZAKMI V2 Parameters and Internals

Model Type 
text generation, chatbot
Use Cases 
Areas:
research, chatbot development
Applications:
cozy free chatbot
Primary Use Cases:
Chatbot conversations
Limitations:
Not good at math, riddles or being extremely smart., Repetition issues without penalty settings., Handling of long system messages.
Considerations:
Using the recommended prompt format can improve performance.
Additional Notes 
Base Yi-6B model is known to have refusals which may affect this model.
Training Details 
Data Sources:
AEZAKMI v2 dataset
Methodology:
Fine-tuned
Context Length:
200000
Model Architecture:
llamafied
Input Output 
Input Format:
ChatML format
Accepted Modalities:
text
Output Format:
text
Performance Tips:
Set repetition penalty to 1.05 and use temperature 1.2 to avoid repetition and improve performance.
LLM NameYi 6B 200K AEZAKMI V2
Repository ๐Ÿค—https://huggingface.co/adamo1139/Yi-6B-200K-AEZAKMI-v2 
Model Size6b
Required VRAM12.1 GB
Updated2025-02-05
Maintaineradamo1139
Model Typellama
Model Files  4.9 GB: 1-of-3   5.0 GB: 2-of-3   2.2 GB: 3-of-3
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length200000
Model Max Length200000
Transformers Version4.35.0
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-6B-200K-AEZAKMI-v2.

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227