Text Generation
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text-generation-inference
Instructions to use ByteWave/prompt-generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ByteWave/prompt-generator with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ByteWave/prompt-generator")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("ByteWave/prompt-generator") model = AutoModelForCausalLM.from_pretrained("ByteWave/prompt-generator", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ByteWave/prompt-generator with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ByteWave/prompt-generator" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ByteWave/prompt-generator", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/ByteWave/prompt-generator
- SGLang
How to use ByteWave/prompt-generator 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 "ByteWave/prompt-generator" \ --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": "ByteWave/prompt-generator", "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 "ByteWave/prompt-generator" \ --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": "ByteWave/prompt-generator", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use ByteWave/prompt-generator with Docker Model Runner:
docker model run hf.co/ByteWave/prompt-generator
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Welcome to the official repository of Prompt Generator, a powerful tool for effortlessly generating prompts for Large Language Models (LLMs) by PulsarAI.
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## About Prompt Generator
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Prompt Generator is designed to streamline the process of generating text prompts for LLMs. Whether you are a content creator, researcher, or developer, this tool empowers you to create effective prompts quickly and efficiently.
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## Features
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- Easy-to-use interface
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- Fast prompt generation
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- Support for multiple languages
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- API integration for seamless use in your applications
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## Installation
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You can install Prompt Generator using pip:
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```bash
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pip install prompt-generator
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---
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license: cc-by-nc-4.0
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datasets:
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- fka/awesome-chatgpt-prompts
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- PulsarAI/awesome-chatgpt-prompts-advanced
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language:
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- en
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pipeline_tag: text-generation
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tags:
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- ChatGPT
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- Llama
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- Agents
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- LLMs
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---
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# Prompt Generator by PulsarAI:
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Welcome to the official repository of Prompt Generator, a powerful tool for effortlessly generating prompts for Large Language Models (LLMs) by PulsarAI.
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## About Prompt Generator:
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Prompt Generator is designed to streamline the process of generating text prompts for LLMs. Whether you are a content creator, researcher, or developer, this tool empowers you to create effective prompts quickly and efficiently.
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## Features:
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- Easy-to-use interface
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- Fast prompt generation
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- Support for multiple languages
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- API integration for seamless use in your applications
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## Training:
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This model trained on ```Google Colab T4```
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Loss Graph:
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