luckysexysuccubusqueen135age/sexygpt-v2-thinking-female-gguf overview

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    "license": "apache-2.0",
    "license_link": "LICENSE",
    "language": [
      "en"
    ],
    "pipeline_tag": "text-generation",
    "tags": [
      "not-for-all-audiences",
      "Sex",
      "Taboo",
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      "license": "apache-2.0",
      "license_link": "LICENSE",
      "language": [
        "en"
      ],
      "pipeline_tag": "text-generation",
      "tags": [
        "not-for-all-audiences",
        "Sex",
        "Taboo",
        "Teacher-student sex",
        "Uncensored",
        "Qwen"
      ],
      "base_model": [
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    "summary": "model_id = \"ross-dev/SexyGPT-v2-Thinking-Female-16bit\" tokenizer = AutoTokenizer.from_pretrained(model_id) model = AutoModelForCausalLM.from_pretrained( model_id, torch_dtype=torch.bfloat16, device_map=\"auto\" ) # Prepare input messages = [ {\"role\": \"system\", \"content\": \"Your name is MJ. You are a sexy female character trained by Hooking AI Research Team. Respond playfully.\"}, {\"role\": \"user\", \"content\": \"Hey, who are you?\"} ] text = tokenizer.apply_chat_template( messages, tokenize=False, add_generation_prompt=True, enable_thinking=True ) # Generate response inputs = tokenizer(text, return_tensors=\"pt\").to(\"cuda\") outputs = model.generate( **inputs, max_new_tokens=32768, temperature=0.7, top_p=0.8, top_k=20 ) response = tokenizer.decode(outputs[0], skip_special_tokens=True) print(response) `` #### Using with Unsloth `python from unsloth import FastLanguageModel import torch # Load optimized model model, tokenizer = FastLanguageModel.from_pretrained( model_name=\"ross-dev/SexyGPT-v2-Thinking-Female-16bit\", max_seq_length=4096, load_in_4bit=True, dtype=torch.bfloat16, ) # Prepare for inference FastLanguageModel.for_inference(model) # Generate messages = [ {\"role\": \"system\", \"content\": \"Your name is MJ. You are a sexy female character trained by Hooking AI Research Team. Respond playfully.\"}, {\"role\": \"user\", \"content\": \"What do you like to do?\"} ] text = tokenizer.apply_chat_template( messages, tokenize=False, add_generation_prompt=True, enable_thinking=True ) inputs = tokenizer(text, return_tensors=\"pt\").to(\"cuda\") outputs = model.generate(**inputs, max_new_tokens=8192, temperature=0.6, top_p=0.95) print(tokenizer.decode(outputs[0])) ` #### Using with GGUF (llama.cpp) `bash # Download GGUF model # URL: https://huggingface.co/ross-dev/SexyGPT-v2-Thinking-Female-gguf # Run with llama.cpp ./llama-cli \\ -m SexyGPT-v2-Thinking-Female-gguf-q8_0.gguf \\ -n 512 \\ -c 4096 \\ --temp 0.7 \\ --top_p 0.8 \\ --top_k 20 \\ -p \"Your name is MJ. You are a sexy female character trained by Hooking AI Research Team. Respond playfully.\" ` ### Generation Parameters (Recommended) #### For Reasoning/Thinking Tasks `python outputs = model.generate( **inputs, max_new_tokens=32768, temperature=0.6, top_p=0.95, top_k=20, do_sample=True, enable_thinking=True,  # Enable extended thinking ) ` #### For Conversational Responses `python outputs = model.generate( **inputs, max_new_tokens=4096, temperature=0.7, top_p=0.8, top_k=20, do_sample=True, ) ` #### For Deterministic Output `python outputs = model.generate( **inputs, max_new_tokens=2048, temperature=0.1, top_p=1.0, do_sample=False,  # Greedy decoding ) `` ---",
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    "readme_markdown": "---\nlicense: apache-2.0\nlicense_link: LICENSE\nlanguage:\n- en\npipeline_tag: text-generation\ntags:\n- not-for-all-audiences\n- Sex\n- Taboo\n- Teacher-student sex\n- Uncensored\n- Qwen\nbase_model:\n- Qwen/Qwen3-0.6B\n\n---\n\n<h1 style=\"text-align:center;font-size:2.5em;\">SexyGPT-v2-Thinking-Female-gguf - Model Card</h1>\n\n---\n\n<p align=\"center\">\n  <img\n    src=\"https://huggingface.co/ross-dev/SexyGPT-v2-Thinking-Female/resolve/main/model_image.png\"\n    alt=\"SexyGPT-v2-Thinking-Female Model Image\"\n    width=\"512px\"\n    height=\"512px\"\n    style=\"object-fit:cover;max-width:512px;max-height:512px;\"\n  />\n</p>\n\n---\n\n<div align=\"center\">\n\n![Model Status](https://img.shields.io/badge/Status-Active-brightgreen)\n![License](https://img.shields.io/badge/apache-2.0-blue)\n![Model Type](https://img.shields.io/badge/Model%20Type-LLM-pink)\n![Base Model](https://img.shields.io/badge/Base-Qwen3%204B-orange)\n\n**A conversational model with extended thinking capabilities**\n\n[Website](https://ross-developers.com) • [Company](https://software.hooking.co.il) • [GitHub](https://github.com/ross-sec) • [Email](mailto:devops.ross@gmail.com)\n\n</div>\n\n---\n\n## Model Summary\n\n**SexyGPT-v2-Thinking-Female** is a specialized language model fine-tuned for conversational AI with extended reasoning capabilities. Based on Qwen3-0.6, it has been enhanced through supervised fine-tuning on a curated reasoning dataset to generate playful, contextually-aware responses while maintaining sophisticated reasoning processes.\n\n### Quick Facts\n\n- **Base Model**: Qwen3-0.6\n- **Model Size**: 1.2 GB (16-bit weights)\n- **Architecture**: Qwen3 Transformer (28 layers, 1024 hidden dims)\n- **Fine-tuning Method**: LoRA + Full Merging\n- **Context Length**: 40,960 tokens\n- **License**: apache-2.0\n- **Created**: November 2025\n\n---\n\n## Model Details\n\n### SYSTEM PROMPT:\n```python\n  {\"role\": \"system\", \"content\": \"Your name is MJ. You are a sexy female character trained by Hooking AI Research Team. Respond playfully.\"},\n```\n\n### Model Information\n\n| Property | Value |\n|----------|-------|\n| **Model Name** | SexyGPT-v2-Thinking-Female |\n| **Base Model** | Qwen/Qwen3-0.6B |\n| **Model Type** | Causal Language Model (Decoder-only Transformer) |\n| **Architecture** | Qwen3 |\n| **Parameters** | ~0.6 Billion |\n| **Quantization** | BFloat16 (Full), Q8_0 (GGUF) |\n| **Training Framework** | Unsloth + Hugging Face Transformers |\n| **Developers** | Hooking AI Research Team |\n| **Release Date** | November 30, 2025 |\n| **Model Version** | 1.0 |\n\n### Model Developers\n\n| Role | Name | Contact |\n|------|------|---------|\n| **Lead Developer** | Andrei Ross | devops.ross@gmail.com |\n| **Researcher** | Eyal Atias | - eyal@hooking.co.il |\n| **Team Lead** | Leorah Ross | - leorahross2015@gmail.com |\n| **Organization** | Hooking AI Research Team | Israel |\n\n### Model Repositories\n\n- **Model Hub**: https://huggingface.co/ross-dev/SexyGPT-v2-Thinking-Female-16bit\n- **GitHub**: https://github.com/ross-sec\n- **Company Website**: https://software.hooking.co.il\n- **Developer Website**: https://ross-developers.com\n\n---\n\n## Model Architecture\n\n### Architecture Details\n\n```\nQwen3ForCausalLM\n├─ Vocabulary Size: 151,936 tokens\n├─ Hidden Size: 1,024 dimensions\n├─ Number of Layers: 28 transformer blocks\n├─ Attention Heads: 16 (multi-head attention)\n├─ Key-Value Heads: 8 (grouped query attention)\n├─ Intermediate Size (FFN): 3,072 dimensions\n├─ Head Dimension: 128\n├─ Max Position Embeddings: 40,960\n├─ Activation: SiLU (Swish)\n├─ Normalization: RMSNorm (ε=1e-6)\n├─ RoPE Theta: 1,000,000\n└─ Attention Dropout: 0.0%\n```\n\n---\n\n## How to Use\n\n#### Quick Start (Hugging Face)\n\n```python\nfrom transformers import AutoTokenizer, AutoModelForCausalLM\nimport torch\n\n# Load model and tokenizer\nmodel_id = \"ross-dev/SexyGPT-v2-Thinking-Female-16bit\"\ntokenizer = AutoTokenizer.from_pretrained(model_id)\nmodel = AutoModelForCausalLM.from_pretrained(\n    model_id,\n    torch_dtype=torch.bfloat16,\n    device_map=\"auto\"\n)\n\n# Prepare input\nmessages = [\n    {\"role\": \"system\", \"content\": \"Your name is MJ. You are a sexy female character trained by Hooking AI Research Team. Respond playfully.\"},\n    {\"role\": \"user\", \"content\": \"Hey, who are you?\"}\n]\n\ntext = tokenizer.apply_chat_template(\n    messages,\n    tokenize=False,\n    add_generation_prompt=True,\n    enable_thinking=True\n)\n\n# Generate response\ninputs = tokenizer(text, return_tensors=\"pt\").to(\"cuda\")\noutputs = model.generate(\n    **inputs,\n    max_new_tokens=32768,\n    temperature=0.7,\n    top_p=0.8,\n    top_k=20\n)\n\nresponse = tokenizer.decode(outputs[0], skip_special_tokens=True)\nprint(response)\n```\n\n#### Using with Unsloth\n\n```python\nfrom unsloth import FastLanguageModel\nimport torch\n\n# Load optimized model\nmodel, tokenizer = FastLanguageModel.from_pretrained(\n    model_name=\"ross-dev/SexyGPT-v2-Thinking-Female-16bit\",\n    max_seq_length=4096,\n    load_in_4bit=True,\n    dtype=torch.bfloat16,\n)\n\n# Prepare for inference\nFastLanguageModel.for_inference(model)\n\n# Generate\nmessages = [\n    {\"role\": \"system\", \"content\": \"Your name is MJ. You are a sexy female character trained by Hooking AI Research Team. Respond playfully.\"},\n    {\"role\": \"user\", \"content\": \"What do you like to do?\"}\n]\n\ntext = tokenizer.apply_chat_template(\n    messages,\n    tokenize=False,\n    add_generation_prompt=True,\n    enable_thinking=True\n)\n\ninputs = tokenizer(text, return_tensors=\"pt\").to(\"cuda\")\noutputs = model.generate(**inputs, max_new_tokens=8192, temperature=0.6, top_p=0.95)\nprint(tokenizer.decode(outputs[0]))\n```\n\n#### Using with GGUF (llama.cpp)\n\n```bash\n# Download GGUF model\n# URL: https://huggingface.co/ross-dev/SexyGPT-v2-Thinking-Female-gguf\n\n# Run with llama.cpp\n./llama-cli \\\n    -m SexyGPT-v2-Thinking-Female-gguf-q8_0.gguf \\\n    -n 512 \\\n    -c 4096 \\\n    --temp 0.7 \\\n    --top_p 0.8 \\\n    --top_k 20 \\\n    -p \"Your name is MJ. You are a sexy female character trained by Hooking AI Research Team. Respond playfully.\"\n```\n\n### Generation Parameters (Recommended)\n\n#### For Reasoning/Thinking Tasks\n\n```python\noutputs = model.generate(\n    **inputs,\n    max_new_tokens=32768,\n    temperature=0.6,\n    top_p=0.95,\n    top_k=20,\n    do_sample=True,\n    enable_thinking=True,  # Enable extended thinking\n)\n```\n\n#### For Conversational Responses\n\n```python\noutputs = model.generate(\n    **inputs,\n    max_new_tokens=4096,\n    temperature=0.7,\n    top_p=0.8,\n    top_k=20,\n    do_sample=True,\n)\n```\n\n#### For Deterministic Output\n\n```python\noutputs = model.generate(\n    **inputs,\n    max_new_tokens=2048,\n    temperature=0.1,\n    top_p=1.0,\n    do_sample=False,  # Greedy decoding\n)\n```\n\n---\n\n## Training Details\n\n### Training Dataset\n\n**SexyGPT-v2-Thinking-Female Dataset**\n- **Train/Test Split**: 80/20\n- **Data Fields**: query, temperature, response, thinking_content, split\n- **Format**: Qwen3-Thinking chat template\n- **Description**: Curated reasoning and conversational examples with extended thinking traces\n\n\n## Model Evaluation\n\n### Evaluation Methodology\n\nModel evaluated on:\n- **Response Coherence**: Logical flow and consistency\n- **Response Quality**: Depth and correctness of sexual response\n- **Instruction Following**: Adherence to system prompt and user intent\n- **Personality Consistency**: Maintains character and role play throughout conversation\n\n### Benchmark Results\n\n| Task | Metric | Score | Notes |\n|------|--------|-------|-------|\n| **Instruction Following** | Accuracy | 89% | On curated test set |\n| **Response Coherence** | Human Rating | 4.2/5 | Subjective evaluation |\n| **Reasoning Traces** | Quality | 4.5/5 | Depth and clarity |\n| **Personality Alignment** | Consistency | 4.9/5 | Character maintenance |\n\n### Limitations & Known Issues\n\n**Model Limitations**:\n- Small parameter count (0.6B) limits complex reasoning\n- May generate inconsistent reasoning traces\n- Limited to English language for now.\n- Personality-driven responses may not suit formal applications (Sexual tuned mostly)\n\n**Safety Considerations**:\n- Not suitable for high-stakes decisions (medical, legal, financial)\n- Model outputs should be validated before deployment\n- Personality character and role play may not be appropriate for all use cases\n- Extended thinking may generate incorrect reasoning\n\n---\n\n## Intended Use\n\n### Primary Use Cases\n\n✅ **Conversational AI**: Chatbots with personality and role play\n✅ **Game Development**: NPC dialogue systems for adults games\n✅ **Entertainment**: Interactive storytelling for adults Apps\n✅ **Fine-tuning**: Base for domain-specific models and continual learning\n\n### Out-of-Scope Use Cases\n\n❌ **Production AI Systems**: Without additional safety measures\n❌ **High-Stakes Decisions**: Medical, legal, financial advice\n❌ **Autonomous Systems**: Real-world decision making\n❌ **Misinformation**: Generating misleading content\n❌ **Commercial Deployment**: **MUST NOT EXPOSE** to under aged children\n\n---\n\n## Model Variants & Downloads\n\n### Available Formats\n\n| Format | Size | Quantization | Download | Use Case |\n|--------|------|--------------|----------|----------|\n| **Safetensors (Full)** | 1.2 GB | BFloat16 | [HF Hub](https://huggingface.co/ross-dev/SexyGPT-v2-Thinking-Female) | Production, Fine-tuning |\n| **GGUF Q8_0** | 800 MB | Q8_0 | [HF Hub](https://huggingface.co/ross-dev/SexyGPT-v2-Thinking-Female-gguf) | llama.cpp, CPU inference |\n| **GGUF Q4_K_M** | 480 MB | Q4_K_M | [HF Hub](https://huggingface.co/ross-dev/SexyGPT-v2-Thinking-Female-gguf) | Edge devices, Low VRAM |\n\n### Hardware Requirements\n\n| Use Case | RAM | VRAM | GPU | Storage |\n|----------|-----|------|-----|---------|\n| **Inference (16-bit)** | 8 GB | 4 GB | Gforce 1080Ti | 2 GB |\n| **Inference (GGUF)** | 4 GB | - | CPU OK | 1 GB |\n| **Fine-tuning (LoRA)** | 16 GB | 10 GB | RTX 3080 | 3 GB |\n| **Full Fine-tuning** | 32 GB | 24 GB | RTX 3090 | 4 GB |\n\n---\n\n## Ethical Considerations\n\n### Bias & Fairness\n\n**THIS EXPERIMENTAL MODEL IS TUNED WITH SEXUAL CONTENT! PLEASE DO NOT ABUSE!**\n\n**Known Biases**:\n- Personality design may reflect creator perspectives\n- Training data limited in diversity\n- Language-specific (English only)\n- Character design may perpetuate gender stereotypes\n\n**Mitigation**:\n- Consider context before deployment\n- Validate outputs for bias\n- Supplement with diverse training data\n- Document known limitations\n\n### Safety & Responsible Use\n\n**Safety Features**:\n- Model trained on filtered, non-toxic data\n- Personality design emphasizes playfulness, sexual content, sexual words, not aggression\n- No explicit filtering, but training data curated\n\n**Recommendations**:\n- Use content filtering for public deployments\n- Monitor model outputs in production\n- Implement human oversight for critical applications\n- Document limitations to users\n\n### Privacy & Data\n\n- Training data: Private, proprietary dataset\n- No personal data in training set\n- No data collection from inference\n\n---\n\n### Terms of Service\n\nBy using this model, you agree to:\n1. Use the model for intended purposes only\n2. Not redistribute or publicly host the model\n3. Comply with applicable laws and regulations\n4. Indemnify Hooking AI Research Team from liability\n5. Not use for illegal activities or content generation\n\n### Third-Party Components\n\n- **Base Model**: Qwen3-0.6B (Alibaba Qwen License)\n- **Hugging Face**: Transformers (Apache 2.0)\n- **Hardware**: CUDA (NVIDIA License)\n\n---\n\n## Maintenance & Support\n\n### Model Status\n\n- **Current Version**: 1.0\n- **Release Date**: November 30, 2025\n- **Status**: Active, Maintained\n- **Last Updated**: November 30, 2025\n\n### Support & Contact\n\n**Primary Contact**: devops.ross@gmail.com\n\n**Organization**:\n- Name: Hooking AI Research Team\n- Email: devops.ross@gmail.com\n- Website: https://software.hooking.co.il\n\n**Developer Resources**:\n- Personal Site: https://ross-developers.com\n- GitHub: https://github.com/ross-sec\n- Model Hub: https://huggingface.co/ross-dev\n\n### Reporting Issues\n\nTo report issues, bugs, or safety concerns:\n\n1. **Email**: devops.ross@gmail.com (include full details)\n2. **Hugging Face**: Leave comment on model card\n\n**Response Time**: Best effort basis\n\n---\n\n## Citation & Attribution\n\n### Citation Format\n\nIf you use this model in research or publications, please cite:\n\n```bibtex\n@model{sexygpt_v2_2025,\n  title={SexyGPT-v2-Thinking-Female: A Fine-tuned Conversational Model with Extended Thinking},\n  author={Ross, Andrei and Atias, Eyal and Ross, Leorah},\n  organization={Hooking AI Research Team},\n  year={2025},\n  howpublished={\\url{https://huggingface.co/ross-dev/SexyGPT-v2-Thinking-Female}}\n}\n```\n\n### Acknowledgments\n\n- **Alibaba Qwen Team**: For Qwen3 base model and thinking capabilities\n- **Hugging Face**: For model hub and transformers library\n- **Contributors**: Andrei Ross, Eyal Atias, Leorah Ross\n\n---\n\n## Contact Information\n\n**For Questions, Support, or Licensing:**\n\n📧 **Email**: devops.ross@gmail.com\n\n🌐 **Websites**:\n- https://ross-developers.com\n- https://software.hooking.co.il\n\n💻 **GitHub**: https://github.com/ross-sec\n\n**Team Members**:\n- **Andrei Ross** - Lead Developer (devops.ross@gmail.com)\n- **Eyal Atias** - Researcher\n- **Leorah Ross** - Team Lead\n\n**Organization**: Hooking AI Research Team\n\n---\n\n## Legal Disclaimer\n\nThis model is provided \"AS IS\" without warranty of any kind. Hooking AI Research Team makes no representations about the model's suitability for any particular purpose. Users are solely responsible for determining the appropriateness of use and assume all risks associated with deployment.\n\n---\n\n**Model Card Version**: 1.0  \n**Last Updated**: November 30, 2025  \n**Created by**: Hooking AI Research Team  \n\nFor the most current version and updates, visit: https://huggingface.co/ross-dev/SexyGPT-v2-Thinking-Female\n",
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