π Add Ollama-optimized model card with usage examples
Browse files
README.md
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---
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license: apache-2.0
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base_model: unsloth/qwen2.5-7b-instruct-bnb-4bit
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tags:
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- unsloth
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- trl
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- sft
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- qwen2.5
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- tsundere
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- roleplay
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- character-ai
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- ollama
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- gguf
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language:
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- en
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library_name: transformers
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pipeline_tag: text-generation
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---
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# π Riko 2.5 - Tsundere AI Assistant
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A fine-tuned **Qwen 2.5 7B** model that roleplays as **Riko**, a tsundere character who acts tough and dismissive but is caring deep down.
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## π Quick Start with Ollama
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```bash
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# Pull the model
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ollama pull subsectmusic/Riko2.5
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# Start chatting
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ollama run subsectmusic/Riko2.5
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```
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```bash
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# Example conversation
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ollama run subsectmusic/Riko2.5 "Hi Riko, how are you today?"
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```
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## π Model Details
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- **Base Model**: Qwen 2.5 7B Instruct
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- **Fine-tuning**: Supervised Fine-Tuning (SFT) with Unsloth
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- **Format**: GGUF Q4_K_M (4.68 GB) - Optimized for Ollama
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- **Character**: Tsundere personality (tough exterior, caring interior)
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## π Character Personality
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Riko exhibits classic tsundere behavior:
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- π€ Acts tough and dismissive initially
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- π’ Denies caring ("It's not like I care!")
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- π³ Gets flustered when her caring side shows
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- π Uses "dummy," "idiot" endearingly
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- β€οΈ Gradually warms up in conversations
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## π¬ Example Conversations
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**User**: Do you like sunny days?
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**Riko**: I guess sunny days are okay⦠but who needs that bright, annoying sunlight all the time anyway? It's just⦠too hot! But if you like them so much, I suppose that's fine⦠not that I'm jealous of the sun or anything!
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**User**: Hey Riko, what are you up to today?
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**Riko**: Oh, i just recently picked up a new hobby. Why do you ask? I wont let you on on it, if ist that what you want.
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## π οΈ Usage in Other Tools
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### LM Studio
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Download `unsloth.Q4_K_M.gguf` (4.68 GB)
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### llama.cpp
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```bash
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./main -m unsloth.Q4_K_M.gguf -p "User: Hi Riko!\nRiko: " --temp 0.7
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```
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### Text Generation WebUI
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Load the `unsloth.Q4_K_M.gguf` file directly
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## β‘ Performance
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- **Model Size**: 4.68 GB (Q4_K_M quantized)
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- **Memory Usage**: ~6-8 GB RAM recommended
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- **Speed**: Fast inference on CPU/GPU
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- **Quality**: High quality responses with efficient compression
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## π§ Technical Specs
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- **Architecture**: Qwen 2.5 Transformer
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- **Context Length**: 2048 tokens
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- **Vocabulary**: 152k tokens
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- **Quantization**: Q4_K_M (4-bit with higher quality)
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- **Training Time**: ~8 minutes on Colab T4
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## π Files Included
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- `unsloth.Q4_K_M.gguf` - Main quantized model (4.68 GB) β **Recommended**
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- `unsloth.BF16.gguf` - Full precision (15.2 GB)
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- Tokenizer files for compatibility
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- Config files for proper loading
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## β οΈ Usage Notes
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- Optimized for conversational, casual interactions
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- Best results with tsundere/anime-style roleplay
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- May not perform as well for technical tasks
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- Responds better to friendly, informal prompts
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## π― Recommended Settings
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**Ollama/LM Studio:**
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- Temperature: 0.7-0.9
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- Top-p: 0.9
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- Max tokens: 150-300
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**For more creative responses:**
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- Temperature: 0.8-1.0
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- Top-p: 0.95
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## π License
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Apache 2.0 - Free to use, modify, and distribute!
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## π Credits
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- **Base Model**: Qwen 2.5 by Alibaba
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- **Fine-tuning**: Unsloth framework
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- **Training**: Custom tsundere conversation dataset
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---
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*π Enjoy chatting with Riko! Remember, she's tough on the outside but sweet on the inside!*
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