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, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("prithivMLmods/Stark-Prompt-Extender") model = AutoModelForMultimodalLM.from_pretrained("prithivMLmods/Stark-Prompt-Extender") - 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
Update README.md
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@@ -16,3 +16,19 @@ The "Prompt Extender" is a tool or concept that can be applied in various fields
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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.
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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.
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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.
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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.
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## Optimization Prompt
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Relevance: Ensure the extended content remains relevant to the original prompt.
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Clarity: Maintain clear and coherent communication with each addition.
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Depth vs. Breadth: Decide whether to explore specific aspects deeply or broaden the scope.
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Creativity: Encourage imaginative approaches to enrich the content and engage the audience.
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Audience Consideration: Tailor the content to suit the preferences and knowledge level of the audience.
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Accuracy: Verify that additional information provided is factually correct.
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Consistency: Maintain consistency in tone, style, and messaging throughout.
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Purpose: Align the content with the intended goal, whether to inform, entertain, persuade, or inspire.
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Feedback Loop: Gather input and insights to iteratively refine the content.
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Ethical Considerations: Respect privacy, cultural norms, and ethical guidelines throughout the expansion process.
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By considering these parameters, users can effectively utilize prompt extenders to generate valuable and engaging content.
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