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CoT 2.5 by c10x

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  Merged Model   Arxiv:2306.01708   Autotrain compatible Base model:eva-unit-01/eva-qwe... Base model:happzy2633/qwen2.5-... Base model:humanllms/human-lik...   Base model:qwen/qwen2.5-7b Base model:qwen/qwen2.5-coder-...   Codegen   Conversational   Endpoints compatible   Qwen2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/c10x/CoT-2.5 

CoT 2.5 Benchmarks

LLME Score: 0.23886
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
CoT 2.5 (c10x/CoT-2.5)

CoT 2.5 Parameters and Internals

Model Type 
text generation
Additional Notes 
The model is a merge of multiple pre-trained language models using mergekit.
LLM NameCoT 2.5
Repository 🤗https://huggingface.co/c10x/CoT-2.5 
Base Model(s)  Qwen/Qwen2.5-7B   EVA-UNIT-01/EVA-Qwen2.5-7B-v0.1   Qwen/Qwen2.5-Coder-7B   HumanLLMs/Humanish-Qwen2.5-7B-Instruct   happzy2633/qwen2.5-7b-ins-v3   Qwen/Qwen2.5-7B   EVA-UNIT-01/EVA-Qwen2.5-7B-v0.1   Qwen/Qwen2.5-Coder-7B   HumanLLMs/Humanish-Qwen2.5-7B-Instruct   happzy2633/qwen2.5-7b-ins-v3
Merged ModelYes
Model Size7b
Required VRAM15.2 GB
Updated2024-10-29
Maintainerc10x
Model Typeqwen2
Model Files  5.0 GB: 1-of-4   4.9 GB: 2-of-4   5.0 GB: 3-of-4   0.3 GB: 4-of-4
Generates CodeYes
Model ArchitectureQwen2ForCausalLM
Context Length131072
Model Max Length131072
Transformers Version4.45.1
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace

Best Alternatives to CoT 2.5

Best Alternatives
Context / RAM
Downloads
Likes
Qwen2.5 7B CySecButler V0.1128K / 15.2 GB492
StockQwen 2.5 7B128K / 15.2 GB972
Mergekit Ties Uqhfast128K / 15.2 GB260
CoT 2.5128K / 15.2 GB260
Mergekit Ties Uqhfast128K / 15.2 GB130
Qwen2.5 Coder 7B Instruct32K / 15.2 GB161896365
Qwen2.5 Coder 7B32K / 15.2 GB3229881
Qwen2.5 Coder 7B Instruct Ties32K / 15.2 GB3120
MilkDropLM 7B V0.332K / 15.2 GB4911
Qwen2.5 Coder 7B Instruct32K / 15.3 GB37924
Note: green Score (e.g. "73.2") means that the model is better than c10x/CoT-2.5.

Rank the CoT 2.5 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241217
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