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Qwen2.5 Sex by ystemsrx

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Qwen2.5 Sex is an open-source language model by ystemsrx. Features: 1.5b LLM, VRAM: 3.1GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.19.

  Adapter-transformers Base model:adapter:qwen/qwen2.... Base model:qwen/qwen2.5-1.5b-i...   Conversational Dataset:ystemsrx/bad data alpa... Dataset:ystemsrx/erotic litera...   Dataset:ystemsrx/toxic-all   F16   Ggml   Gguf   Instruct   Not-for-all-audiences   Quantized   Qwen2   Region:us   Safetensors   Zh
Model Card on HF 🤗: https://huggingface.co/ystemsrx/Qwen2.5-Sex 

Qwen2.5 Sex Benchmarks

LLME Score: 0.18551
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Qwen2.5 Sex (ystemsrx/Qwen2.5-Sex)
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Qwen2.5 Sex Parameters and Internals

LLM NameQwen2.5 Sex
Repository 🤗https://huggingface.co/ystemsrx/Qwen2.5-Sex 
Base Model(s)  Qwen/Qwen2.5-1.5B-Instruct   Qwen/Qwen2.5-1.5B-Instruct
Model Size1.5b
Required VRAM3.1 GB
Updated2025-09-23
Maintainerystemsrx
Model Typeqwen2
Instruction-BasedYes
Model Files  3.1 GB   3.1 GB
Supported Languageszh
GGML QuantizationYes
GGUF QuantizationYes
Quantization Typeggml|gguf
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.44.2
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typebfloat16
Errorsreplace

Best Alternatives to Qwen2.5 Sex

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Context / RAM
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Atem V1.1.5B32K / 1 GB1460
Qwen2 1.5B Instruct GGUF32K / 0.7 GB3710
Qwen2 1.5B Instruct GGUF32K / 0.7 GB860
Qwen2.5 Coder 1.5B NL Java32K / 3.1 GB1310
Legal Qwen2.5 1.5B Finetuned32K / 3.1 GB100
Qwen2.5 1.5B Legal Sft32K / 3.1 GB390
Qwen2.5 1.5B Legal Id Sft32K / 3.1 GB240
Qwen Legal SFT Dicoding Final32K / 3.1 GB130
Legal Chatbot Qwen2.5 1.5B Sft32K / 3.1 GB100
Qwen2.5 1.5B Legal ID Chatbot32K / 3.1 GB540
Note: green Score (e.g. "73.2") means that the model is better than ystemsrx/Qwen2.5-Sex.

Rank the Qwen2.5 Sex 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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