Instructions to use Den4ikAI/ruT5-small-interpreter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Den4ikAI/ruT5-small-interpreter with Transformers:

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

pipe = pipeline("text-generation", model="Den4ikAI/ruT5-small-interpreter")

# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("Den4ikAI/ruT5-small-interpreter")
model = AutoModelForSeq2SeqLM.from_pretrained("Den4ikAI/ruT5-small-interpreter")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Den4ikAI/ruT5-small-interpreter with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Den4ikAI/ruT5-small-interpreter"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Den4ikAI/ruT5-small-interpreter",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Den4ikAI/ruT5-small-interpreter

SGLang

How to use Den4ikAI/ruT5-small-interpreter 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 "Den4ikAI/ruT5-small-interpreter" \
    --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": "Den4ikAI/ruT5-small-interpreter",
		"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 "Den4ikAI/ruT5-small-interpreter" \
        --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": "Den4ikAI/ruT5-small-interpreter",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Den4ikAI/ruT5-small-interpreter with Docker Model Runner:
```
docker model run hf.co/Den4ikAI/ruT5-small-interpreter
```

Den4ikAI commited on Jun 7, 2023

Commit

a99c932

1 Parent(s): 0003f2a

Update README.md

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@@ -1,3 +1,40 @@
 ---
 license: mit
 ---

 ---
 license: mit
+datasets:
+- inkoziev/incomplete_utterance_restoration
+language:
+- ru
+widget:
+- text: '- Как тебя зовут?\n- Иван #'
+- text: '- А живешь где?\n- В Москве #'
+pipeline_tag: text2text-generation
 ---
+# Den4ikAI/ruT5-small-interpreter
+Модель для восстановления фразы с помощью контекста диалога (анафора, эллипсисы, гэппинг), проверки орфографии и нормализации текста диалоговых реплик.
+Больше о задаче [тут](https://huggingface.co/inkoziev/rugpt_interpreter).
+# Пример использования
+```python
+import torch
+from transformers import T5ForConditionalGeneration, T5Tokenizer
+model_name = 'Den4ikAI/ruT5-small-interpreter'
+tokenizer = T5Tokenizer.from_pretrained(model_name)
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model = T5ForConditionalGeneration.from_pretrained(model_name)
+model.eval()
+t5_input = '''- Ты собак любишь?
+- Не люблю я их  #'''
+input_ids = tokenizer(t5_input, return_tensors='pt').input_ids
+out_ids = model.generate(input_ids=input_ids, max_length=100, eos_token_id=tokenizer.eos_token_id, early_stopping=True)
+t5_output = tokenizer.decode(out_ids[0][1:])
+print(t5_output)
+```
+# Citation
+```
+@MISC{Den4ikAI/ruT5-small-interpreter,
+    author  = {Denis Petrov, Ilya Koziev},
+    title   = {Russian conversations interpreter and normalizer},
+    url     = {https://huggingface.co/Den4ikAI/ruT5-small-interpreter},
+    year    = 2023
+}
+```