Text Generation
Transformers
PyTorch
English
t5
text2text-generation
paraphrasing
transformer
text-generation-inference
Instructions to use SRDdev/Paraphrase with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SRDdev/Paraphrase with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="SRDdev/Paraphrase")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("SRDdev/Paraphrase") model = AutoModelForSeq2SeqLM.from_pretrained("SRDdev/Paraphrase") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use SRDdev/Paraphrase with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "SRDdev/Paraphrase" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "SRDdev/Paraphrase", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/SRDdev/Paraphrase
- SGLang
How to use SRDdev/Paraphrase 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 "SRDdev/Paraphrase" \ --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": "SRDdev/Paraphrase", "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 "SRDdev/Paraphrase" \ --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": "SRDdev/Paraphrase", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use SRDdev/Paraphrase with Docker Model Runner:
docker model run hf.co/SRDdev/Paraphrase
- Xet hash:
- ccaf0e2f55e14b481e7ccc9baf65ebc5311a2c9b2299ab10ec0da119b06226b3
- Size of remote file:
- 892 MB
- SHA256:
- eef6efe0c2f76b54837f90df73c4dc5586e0ada4d8ed7c337a8c9b3021aed803
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