Instructions to use elizaveta-dev/T5-REF-CORRUPT-EN with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use elizaveta-dev/T5-REF-CORRUPT-EN with Transformers:

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

pipe = pipeline("text-generation", model="elizaveta-dev/T5-REF-CORRUPT-EN")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("elizaveta-dev/T5-REF-CORRUPT-EN")
model = AutoModelForSeq2SeqLM.from_pretrained("elizaveta-dev/T5-REF-CORRUPT-EN", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use elizaveta-dev/T5-REF-CORRUPT-EN with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "elizaveta-dev/T5-REF-CORRUPT-EN"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "elizaveta-dev/T5-REF-CORRUPT-EN",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/elizaveta-dev/T5-REF-CORRUPT-EN

SGLang

How to use elizaveta-dev/T5-REF-CORRUPT-EN 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 "elizaveta-dev/T5-REF-CORRUPT-EN" \
    --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": "elizaveta-dev/T5-REF-CORRUPT-EN",
		"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 "elizaveta-dev/T5-REF-CORRUPT-EN" \
        --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": "elizaveta-dev/T5-REF-CORRUPT-EN",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use elizaveta-dev/T5-REF-CORRUPT-EN with Docker Model Runner:
```
docker model run hf.co/elizaveta-dev/T5-REF-CORRUPT-EN
```

elizaveta-dev commited on Dec 2, 2025

Commit

093ccc2

verified ·

1 Parent(s): 8949aa1

Upload README.md with huggingface_hub

Browse files

Files changed (1) hide show

README.md +1 -1

README.md CHANGED Viewed

@@ -41,7 +41,7 @@ inputs = tokenizer(text, return_tensors="pt")
 outputs = model.generate(**inputs, max_new_tokens=128)
 print(tokenizer.decode(outputs[0], skip_special_tokens=True))
 ## Use-Cases

 outputs = model.generate(**inputs, max_new_tokens=128)
 print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
 ## Use-Cases