Ao Karasu 72B AWQ 4bit by lightblue

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  Merged Model   4-bit   4bit   Autotrain compatible   Awq   Conversational   Endpoints compatible   Quantized   Qwen2   Region:us   Safetensors   Sharded   Tensorflow

Ao Karasu 72B AWQ 4bit Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Ao Karasu 72B AWQ 4bit (lightblue/ao-karasu-72B-AWQ-4bit)

Ao Karasu 72B AWQ 4bit Parameters and Internals

Model Type 
text generation, chatbot
Use Cases 
Areas:
AI assistance
Applications:
chat-based applications
Primary Use Cases:
Conversation with users in various domains
Additional Notes 
The model was trained with a focus on Japanese language proficiency.
Supported Languages 
Japanese (proficient)
Training Details 
Data Sources:
Wikipedia-based QA, technical blogs, Japanese QA site answers, LLM generated prompts and responses, news articles
Data Volume:
1.1 billion characters
Training Time:
~1 day
Hardware Used:
A100 (80GB) GPU
Input Output 
Input Format:
Prompt format using chat template.
Accepted Modalities:
text
Output Format:
Text
LLM NameAo Karasu 72B AWQ 4bit
Repository ๐Ÿค—https://huggingface.co/lightblue/ao-karasu-72B-AWQ-4bit 
Merged ModelYes
Model Size72b
Required VRAM41.3 GB
Updated2024-12-26
Maintainerlightblue
Model Typeqwen2
Model Files  5.0 GB: 1-of-9   5.0 GB: 2-of-9   5.0 GB: 3-of-9   5.0 GB: 4-of-9   5.0 GB: 5-of-9   5.0 GB: 6-of-9   5.0 GB: 7-of-9   3.8 GB: 8-of-9   2.5 GB: 9-of-9
AWQ QuantizationYes
Quantization Typeawq|4bit
Model ArchitectureQwen2ForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.39.0.dev0
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typefloat16
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than lightblue/ao-karasu-72B-AWQ-4bit.

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Instruction Following and Task Automation  
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Data Analysis and Insight Generation  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227