Text Generation
Transformers
PyTorch
Safetensors
English
t5
text2text-generation
text-generation-inference
Instructions to use humarin/chatgpt_paraphraser_on_T5_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use humarin/chatgpt_paraphraser_on_T5_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="humarin/chatgpt_paraphraser_on_T5_base")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("humarin/chatgpt_paraphraser_on_T5_base") model = AutoModelForSeq2SeqLM.from_pretrained("humarin/chatgpt_paraphraser_on_T5_base") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use humarin/chatgpt_paraphraser_on_T5_base with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "humarin/chatgpt_paraphraser_on_T5_base" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "humarin/chatgpt_paraphraser_on_T5_base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/humarin/chatgpt_paraphraser_on_T5_base
- SGLang
How to use humarin/chatgpt_paraphraser_on_T5_base 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 "humarin/chatgpt_paraphraser_on_T5_base" \ --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": "humarin/chatgpt_paraphraser_on_T5_base", "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 "humarin/chatgpt_paraphraser_on_T5_base" \ --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": "humarin/chatgpt_paraphraser_on_T5_base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use humarin/chatgpt_paraphraser_on_T5_base with Docker Model Runner:
docker model run hf.co/humarin/chatgpt_paraphraser_on_T5_base
Fixing the error facing in google colab
#6
by Roy-Pentagon - opened
README.md
CHANGED
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@@ -44,7 +44,7 @@ device = "cuda"
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tokenizer = AutoTokenizer.from_pretrained("humarin/chatgpt_paraphraser_on_T5_base")
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-
model = AutoModelForSeq2SeqLM.from_pretrained("humarin/chatgpt_paraphraser_on_T5_base").to(
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def paraphrase(
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question,
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tokenizer = AutoTokenizer.from_pretrained("humarin/chatgpt_paraphraser_on_T5_base")
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model = AutoModelForSeq2SeqLM.from_pretrained("humarin/chatgpt_paraphraser_on_T5_base").to('cpu')
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def paraphrase(
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question,
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