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Chinese Alpaca Pro 33B Merged by minlik

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Chinese Alpaca Pro 33B Merged is an open-source language model by minlik. Features: 33b LLM, VRAM: 65.7GB, Context: 2K, LLM Explorer Score: 0.08.

  Endpoints compatible   Llama   Pytorch   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/minlik/chinese-alpaca-pro-33b-merged 

Chinese Alpaca Pro 33B Merged Benchmarks

LLME Score: 0.0832
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Chinese Alpaca Pro 33B Merged (minlik/chinese-alpaca-pro-33b-merged)
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Chinese Alpaca Pro 33B Merged Parameters and Internals

Model Type 
text generation, instruction-following
Additional Notes 
The model is designed to continue pre-training for Chinese embedding and uses further instruction datasets for fine-tuning purposes.
Input Output 
Input Format:
text prompt with Chinese instruction
Accepted Modalities:
text
Output Format:
text completion or response
LLM NameChinese Alpaca Pro 33B Merged
Repository 🤗https://huggingface.co/minlik/chinese-alpaca-pro-33b-merged 
Model Size33b
Required VRAM65.7 GB
Updated2026-04-11
Maintainerminlik
Model Typellama
Model Files  10.1 GB: 1-of-7   10.0 GB: 2-of-7   9.9 GB: 3-of-7   9.9 GB: 4-of-7   9.9 GB: 5-of-7   10.0 GB: 6-of-7   5.9 GB: 7-of-7   10.1 GB: 1-of-7   10.0 GB: 2-of-7   9.9 GB: 3-of-7   9.9 GB: 4-of-7   9.9 GB: 5-of-7   10.0 GB: 6-of-7   6.1 GB: 7-of-7
Model ArchitectureLlamaForCausalLM
Context Length2048
Model Max Length2048
Transformers Version4.29.0.dev0
Tokenizer ClassLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size49954
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than minlik/chinese-alpaca-pro-33b-merged.

Rank the Chinese Alpaca Pro 33B Merged 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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