Instructions to use readerbench/RoGPT2-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use readerbench/RoGPT2-medium with Transformers:

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

pipe = pipeline("text-generation", model="readerbench/RoGPT2-medium")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("readerbench/RoGPT2-medium")
model = AutoModelForCausalLM.from_pretrained("readerbench/RoGPT2-medium")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use readerbench/RoGPT2-medium with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "readerbench/RoGPT2-medium"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "readerbench/RoGPT2-medium",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/readerbench/RoGPT2-medium

SGLang

How to use readerbench/RoGPT2-medium 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 "readerbench/RoGPT2-medium" \
    --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": "readerbench/RoGPT2-medium",
		"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 "readerbench/RoGPT2-medium" \
        --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": "readerbench/RoGPT2-medium",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use readerbench/RoGPT2-medium with Docker Model Runner:
```
docker model run hf.co/readerbench/RoGPT2-medium
```

MihaiAlexandru1606 commited on Oct 19, 2022

Commit

7e75ef2

1 Parent(s): f0587eb

Update README.md

Browse files

Files changed (1) hide show

README.md +13 -4

README.md CHANGED Viewed

@@ -8,9 +8,9 @@ language:
 # RoGPT2: Romanian GPT2 for text generation
 All models are available:
-* [RoBERT-base](https://huggingface.co/readerbench/RoGPT2-base)
-* [RoBERT-medium](https://huggingface.co/readerbench/RoGPT2-medium)
-* [RoBERT-large](https://huggingface.co/readerbench/RoGPT2-large)
 For code and evaluation check out [GitHub](https://github.com/readerbench/RoGPT2).
@@ -191,4 +191,13 @@ Research supported with [Cloud TPUs](https://cloud.google.com/tpu/) from Google'
 ---
-Niculescu, M. A., Ruseti, S., and Dascalu, M. (submitted). RoGPT2: Romanian GPT2 for Text Generation

 # RoGPT2: Romanian GPT2 for text generation
 All models are available:
+* [RoGPT2-base](https://huggingface.co/readerbench/RoGPT2-base)
+* [RoGPT2-medium](https://huggingface.co/readerbench/RoGPT2-medium)
+* [RoGPT2-large](https://huggingface.co/readerbench/RoGPT2-large)
 For code and evaluation check out [GitHub](https://github.com/readerbench/RoGPT2).
 ---
+```bibtex
+@inproceedings{niculescu2021rogpt2,
+  title={RoGPT2: Romanian GPT2 for Text Generation},
+  author={Niculescu, Mihai Alexandru and Ruseti, Stefan and Dascalu, Mihai},
+  booktitle={2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI)},
+  pages={1154--1161},
+  year={2021},
+  organization={IEEE}
+}
+```