Bailong Orpo 7B by INX-TEXT

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  Arxiv:2304.08177   Arxiv:2403.07691   Arxiv:2404.00862   Autotrain compatible Base model:inx-text/bailong-in... Base model:quantized:inx-text/...   Conversational   Endpoints compatible   Gguf   Instruct   Llama   Orpo   Quantized   Region:us   Safetensors   Sharded   Tensorflow

Bailong Orpo 7B Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Bailong Orpo 7B (INX-TEXT/Bailong-orpo-7B)

Bailong Orpo 7B Parameters and Internals

Model Type 
decoder-only transformer architecture
Additional Notes 
The model is trained with context length of 2048 tokens and the training dataset is primarily composed of Traditional Chinese data with a minor portion of English.
Supported Languages 
Traditional Chinese (high), English (medium)
Training Details 
Methodology:
Specially, motivated by the Chinese-LLaMA paper, we implemented QLoRA during the secondary pretraining stage to train the model, as opposed to the standard full-parameter training method. This approach significantly reduces the computational cost while achieving satisfactory model performance simultaneously.
Context Length:
2048
Model Architecture:
Bailong 7B is an autogressive language model with 7B parameters and decoder-only transformer architecture, derived from implementing secondary pretraining on Llama 2 7B with tied embedding and expanded vocabulary.
LLM NameBailong Orpo 7B
Repository ๐Ÿค—https://huggingface.co/INX-TEXT/Bailong-orpo-7B 
Base Model(s)  INX-TEXT/Bailong-instruct-7B   INX-TEXT/Bailong-instruct-7B
Model Size7b
Required VRAM14 GB
Updated2024-12-22
MaintainerINX-TEXT
Model Typellama
Instruction-BasedYes
Model Files  13.9 GB   5.0 GB: 1-of-3   5.0 GB: 2-of-3   4.0 GB: 3-of-3
GGUF QuantizationYes
Quantization Typegguf
Model ArchitectureLlamaForCausalLM
Licensellama2
Context Length4096
Model Max Length4096
Transformers Version4.38.0
Tokenizer ClassLlamaTokenizer
Vocabulary Size59241
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than INX-TEXT/Bailong-orpo-7B.

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241217