Instructions to use prithivMLmods/Stark-Prompt-Extender with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Stark-Prompt-Extender with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="prithivMLmods/Stark-Prompt-Extender")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("prithivMLmods/Stark-Prompt-Extender") model = AutoModelForCausalLM.from_pretrained("prithivMLmods/Stark-Prompt-Extender", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use prithivMLmods/Stark-Prompt-Extender with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "prithivMLmods/Stark-Prompt-Extender" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "prithivMLmods/Stark-Prompt-Extender", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/prithivMLmods/Stark-Prompt-Extender
- SGLang
How to use prithivMLmods/Stark-Prompt-Extender 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 "prithivMLmods/Stark-Prompt-Extender" \ --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": "prithivMLmods/Stark-Prompt-Extender", "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 "prithivMLmods/Stark-Prompt-Extender" \ --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": "prithivMLmods/Stark-Prompt-Extender", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use prithivMLmods/Stark-Prompt-Extender with Docker Model Runner:
docker model run hf.co/prithivMLmods/Stark-Prompt-Extender
| license: creativeml-openrail-m | |
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| ## Prompt Extender | |
| The "Prompt Extender" is a tool or concept that can be applied in various fields, from artificial intelligence to creative writing. Its primary function is to expand or elaborate on a given prompt or idea, providing additional context, details, or possibilities. | |
| Creative Writing: In storytelling, a prompt extender can help writers delve deeper into the world they're creating. For instance, if the initial prompt is "a lone astronaut stranded on a distant planet," the extender could add layers by detailing the alien flora and fauna, the astronaut's internal struggles, or the backstory of how they ended up stranded. | |
| Artificial Intelligence and Natural Language Processing: In AI and NLP, prompt extenders can be used to generate more comprehensive responses. For example, in a chatbot scenario, if a user asks about the weather, the extender could provide not only the current weather but also forecasts, historical data, and related information like best outdoor activities or recommended clothing. | |
| Problem-Solving and Innovation: In business or scientific research, a prompt extender can help brainstorm new ideas or solutions to existing problems. By expanding on the initial prompt, teams can explore different angles, consider alternative approaches, and uncover unexpected insights. | |
| Learning and Education: In classrooms or online courses, prompt extenders can encourage critical thinking and creativity. Students can be given a basic question or problem and then challenged to expand on it, either individually or in groups, fostering collaboration and deeper understanding of the subject matter. | |
| Content Creation: In marketing or content creation, prompt extenders can aid in generating a variety of ideas for articles, videos, or social media posts. Starting with a simple prompt like "summer fashion trends," the extender could suggest specific trends, styling tips, budget-friendly options, or even related topics like skincare or travel. | |
| Personal Development: On a personal level, prompt extenders can be used for journaling, reflection, or goal setting. By expanding on prompts related to self-discovery or personal growth, individuals can gain deeper insights into their emotions, behaviors, and aspirations. | |
| ## Optimization Prompt | |
| Relevance: Ensure the extended content remains relevant to the original prompt. | |
| Clarity: Maintain clear and coherent communication with each addition. | |
| Depth vs. Breadth: Decide whether to explore specific aspects deeply or broaden the scope. | |
| Creativity: Encourage imaginative approaches to enrich the content and engage the audience. | |
| Audience Consideration: Tailor the content to suit the preferences and knowledge level of the audience. | |
| Accuracy: Verify that additional information provided is factually correct. | |
| Consistency: Maintain consistency in tone, style, and messaging throughout. | |
| Purpose: Align the content with the intended goal, whether to inform, entertain, persuade, or inspire. | |
| Feedback Loop: Gather input and insights to iteratively refine the content. | |
| Ethical Considerations: Respect privacy, cultural norms, and ethical guidelines throughout the expansion process. | |
| By considering these parameters, users can effectively utilize prompt extenders to generate valuable and engaging content. |