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Follex 7B by ClaudioItaly

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Follex 7B is an open-source language model by ClaudioItaly. Features: 7b LLM, VRAM: 15.2GB, Context: 32K, Merged, LLM Explorer Score: 0.17.

  Merged Model   Base model:aidc-ai/marco-o1 Base model:bunnycore/fuseqwqen... Base model:happzy2633/qwen2.5-... Base model:prithivmlmods/qwq-l...   Conversational   Endpoints compatible   Qwen2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/ClaudioItaly/Follex-7B 

Follex 7B Benchmarks

LLME Score: 0.16615
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Follex 7B (ClaudioItaly/Follex-7B)
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Follex 7B Parameters and Internals

LLM NameFollex 7B
Repository 🤗https://huggingface.co/ClaudioItaly/Follex-7B 
Base Model(s)  Marco O1   QwQ LCoT 7B Instruct   FuseQwQen 7B   happzy2633/qwen2.5-7b-ins-v3   AIDC-AI/Marco-o1   prithivMLmods/QwQ-LCoT-7B-Instruct   bunnycore/FuseQwQen-7B   happzy2633/qwen2.5-7b-ins-v3
Merged ModelYes
Model Size7b
Required VRAM15.2 GB
Updated2026-05-20
MaintainerClaudioItaly
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
Model ArchitectureQwen2ForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.46.2
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151665
Torch Data Typebfloat16
Errorsreplace

Best Alternatives to Follex 7B

Best Alternatives
Context / RAM
Downloads
Likes
Qwen2.5 7B Preview986K / 15.2 GB100
Qwen2.5 7B Instruct 1M986K / 15.4 GB32350369
Hush Qwen2.5 7B V1.1986K / 15.2 GB191
Hush Qwen2.5 7B V1.2986K / 15.2 GB31
Hush Qwen2.5 7B Preview986K / 15.2 GB400
Hush Qwen2.5 7B V1.4986K / 15.2 GB41
Hush Qwen2.5 7B V1.3986K / 15.2 GB182
Hush Qwen2.5 7B RP V1.4 1M986K / 15.2 GB172
Qwen 2.5 7B Exp Sce986K / 15.2 GB72
Qwen2.5 7B MixStock V0.1986K / 15.2 GB113
Note: green Score (e.g. "73.2") means that the model is better than ClaudioItaly/Follex-7B.

Rank the Follex 7B 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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