Text Generation
Transformers
Safetensors
GGUF
English
gemma3_text
prompt-generation
role-playing
creative-writing
fine-tuned
gemma
stacks
text-generation-inference
Instructions to use gouthamsai78/STACKS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gouthamsai78/STACKS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="gouthamsai78/STACKS")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("gouthamsai78/STACKS") model = AutoModelForCausalLM.from_pretrained("gouthamsai78/STACKS") - llama-cpp-python
How to use gouthamsai78/STACKS with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="gouthamsai78/STACKS", filename="stacks.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use gouthamsai78/STACKS with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf gouthamsai78/STACKS # Run inference directly in the terminal: llama-cli -hf gouthamsai78/STACKS
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf gouthamsai78/STACKS # Run inference directly in the terminal: llama-cli -hf gouthamsai78/STACKS
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf gouthamsai78/STACKS # Run inference directly in the terminal: ./llama-cli -hf gouthamsai78/STACKS
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf gouthamsai78/STACKS # Run inference directly in the terminal: ./build/bin/llama-cli -hf gouthamsai78/STACKS
Use Docker
docker model run hf.co/gouthamsai78/STACKS
- LM Studio
- Jan
- vLLM
How to use gouthamsai78/STACKS with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "gouthamsai78/STACKS" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "gouthamsai78/STACKS", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/gouthamsai78/STACKS
- SGLang
How to use gouthamsai78/STACKS with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "gouthamsai78/STACKS" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "gouthamsai78/STACKS", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "gouthamsai78/STACKS" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "gouthamsai78/STACKS", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Ollama
How to use gouthamsai78/STACKS with Ollama:
ollama run hf.co/gouthamsai78/STACKS
- Unsloth Studio new
How to use gouthamsai78/STACKS with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for gouthamsai78/STACKS to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for gouthamsai78/STACKS to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for gouthamsai78/STACKS to start chatting
- Docker Model Runner
How to use gouthamsai78/STACKS with Docker Model Runner:
docker model run hf.co/gouthamsai78/STACKS
- Lemonade
How to use gouthamsai78/STACKS with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull gouthamsai78/STACKS
Run and chat with the model
lemonade run user.STACKS-{{QUANT_TAG}}List all available models
lemonade list
Update comprehensive model card for STACKS
Browse files
README.md
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@@ -26,7 +26,7 @@ model_type: gemma
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STACKS transforms any role or profession into detailed, engaging prompts perfect for:
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- **Role-playing games** and creative writing
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- **Educational scenarios** and training simulations
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- **Content creation** and storytelling
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- **Character development** exercises
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## 📋 Example Outputs
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**Input:** `"chef"`
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**STACKS Output:** *"Act as a world-renowned chef who specializes in fusion cuisine. You've just opened a new restaurant that combines traditional techniques with molecular gastronomy. Explain your signature dish and the story behind its creation."*
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**Input:** `"time traveler"`
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**STACKS Output:** *"You are a time traveler who has just arrived in the year 2024 from 1850. Describe your amazement at modern technology, but also share wisdom from the past that people today have forgotten."*
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**Input:** `"detective"`
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**STACKS Output:** *"Act as a private detective in 1940s noir-style setting. You've been hired to investigate a mysterious disappearance at a high-society party. Describe the case and your first impressions of the suspects."*
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## 🎭 Supported Role Categories
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STACKS excels at generating prompts for:
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- **Professional Roles**: doctors, lawyers, teachers, engineers, scientists
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- **Creative Roles**: artists, writers, musicians, designers, filmmakers
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- **Historical Figures**: philosophers, explorers, inventors, rulers
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- **Fictional Characters**: superheroes, fantasy characters, sci-fi roles
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- **Specialized Experts**: consultants, coaches, advisors, mentors
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### Training Configuration
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- **Base Model**: google/gemma-3-270m (268M parameters)
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- **Training Type**: Complete fine-tuning (all parameters trainable)
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- **Dataset**: fka/awesome-chatgpt-prompts
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- **Format**: Role → Prompt generation patterns
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- **Precision**: BF16 optimized
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- **Context Length**: 768 tokens
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- **Training Date**: 2025-08-20
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### Model Specifications
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- **Architecture**: Gemma-3
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- **Parameters**: 268,098,176
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- **Format**: Safetensors
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STACKS generates:
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- **Coherent prompts** that match the requested role
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- **Creative scenarios** with engaging storylines
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- **Detailed instructions** for effective role-playing
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- **Varied outputs** avoiding repetitive patterns
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- **Contextually appropriate** content for each role
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---
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**Built with ❤️ by gouthamsai78**
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*Transforming roles into creative prompts, one generation at a time.*
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STACKS transforms any role or profession into detailed, engaging prompts perfect for:
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- **Role-playing games** and creative writing
|
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- **Educational scenarios** and training simulations
|
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- **Content creation** and storytelling
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- **Character development** exercises
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## 📋 Example Outputs
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**Input:** `"chef"`
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**STACKS Output:** *"Act as a world-renowned chef who specializes in fusion cuisine. You've just opened a new restaurant that combines traditional techniques with molecular gastronomy. Explain your signature dish and the story behind its creation."*
|
| 55 |
|
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+
**Input:** `"time traveler"`
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**STACKS Output:** *"You are a time traveler who has just arrived in the year 2024 from 1850. Describe your amazement at modern technology, but also share wisdom from the past that people today have forgotten."*
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+
**Input:** `"detective"`
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**STACKS Output:** *"Act as a private detective in 1940s noir-style setting. You've been hired to investigate a mysterious disappearance at a high-society party. Describe the case and your first impressions of the suspects."*
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## 🎭 Supported Role Categories
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STACKS excels at generating prompts for:
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| 66 |
- **Professional Roles**: doctors, lawyers, teachers, engineers, scientists
|
| 67 |
+
- **Creative Roles**: artists, writers, musicians, designers, filmmakers
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| 68 |
- **Historical Figures**: philosophers, explorers, inventors, rulers
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| 69 |
- **Fictional Characters**: superheroes, fantasy characters, sci-fi roles
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- **Specialized Experts**: consultants, coaches, advisors, mentors
|
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### Training Configuration
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- **Base Model**: google/gemma-3-270m (268M parameters)
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- **Training Type**: Complete fine-tuning (all parameters trainable)
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+
- **Dataset**: fka/awesome-chatgpt-prompts
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- **Format**: Role → Prompt generation patterns
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- **Precision**: BF16 optimized
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- **Context Length**: 768 tokens
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- **Training Date**: 2025-08-20
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### Model Specifications
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- **Architecture**: Gemma-3
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- **Parameters**: 268,098,176
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- **Format**: Safetensors
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STACKS generates:
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- **Coherent prompts** that match the requested role
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+
- **Creative scenarios** with engaging storylines
|
| 97 |
- **Detailed instructions** for effective role-playing
|
| 98 |
- **Varied outputs** avoiding repetitive patterns
|
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- **Contextually appropriate** content for each role
|
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|
|
| 109 |
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---
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+
**Built with ❤️ by gouthamsai78**
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*Transforming roles into creative prompts, one generation at a time.*
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