Instructions to use Vamsi/T5_Paraphrase_Paws with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Vamsi/T5_Paraphrase_Paws with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Vamsi/T5_Paraphrase_Paws")

# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("Vamsi/T5_Paraphrase_Paws")
model = AutoModelForSeq2SeqLM.from_pretrained("Vamsi/T5_Paraphrase_Paws", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Vamsi/T5_Paraphrase_Paws with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Vamsi/T5_Paraphrase_Paws"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Vamsi/T5_Paraphrase_Paws",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Vamsi/T5_Paraphrase_Paws

SGLang

How to use Vamsi/T5_Paraphrase_Paws 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 "Vamsi/T5_Paraphrase_Paws" \
    --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": "Vamsi/T5_Paraphrase_Paws",
		"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 "Vamsi/T5_Paraphrase_Paws" \
        --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": "Vamsi/T5_Paraphrase_Paws",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Vamsi/T5_Paraphrase_Paws with Docker Model Runner:
```
docker model run hf.co/Vamsi/T5_Paraphrase_Paws
```

Vamsi

FrozenWolf commited on Jun 12, 2023

Commit

f8c3ded

1 Parent(s): c6a296c

Update README.md (#2)

Browse files

- Update README.md (46805a927a5cc1843e50f7bf3f620fb554e2b359)

Co-authored-by: Gokul Adethya T <FrozenWolf@users.noreply.huggingface.co>

Files changed (1) hide show

README.md +3 -3

README.md CHANGED Viewed

@@ -6,7 +6,7 @@ tags:
 - Conditional Generation
 inference: false
 ---
 # Paraphrase-Generation
 ## Model description
@@ -14,14 +14,14 @@ inference: false
 T5 Model for generating paraphrases of english sentences. Trained on the [Google PAWS](https://github.com/google-research-datasets/paws) dataset.
 ## How to use
 PyTorch and TF models available
 ```python
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 tokenizer = AutoTokenizer.from_pretrained("Vamsi/T5_Paraphrase_Paws")
-model = AutoModelForSeq2SeqLM.from_pretrained("Vamsi/T5_Paraphrase_Paws")
 sentence = "This is something which i cannot understand at all"

 - Conditional Generation
 inference: false
 ---
 # Paraphrase-Generation
 ## Model description
 T5 Model for generating paraphrases of english sentences. Trained on the [Google PAWS](https://github.com/google-research-datasets/paws) dataset.
 ## How to use
+## Requires sentencepiece: # !pip install sentencepiece
 PyTorch and TF models available
 ```python
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 tokenizer = AutoTokenizer.from_pretrained("Vamsi/T5_Paraphrase_Paws")
+model = AutoModelForSeq2SeqLM.from_pretrained("Vamsi/T5_Paraphrase_Paws").to('cuda')
 sentence = "This is something which i cannot understand at all"