Instructions to use readerbench/RoGPT2-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use readerbench/RoGPT2-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="readerbench/RoGPT2-base")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("readerbench/RoGPT2-base") model = AutoModelForCausalLM.from_pretrained("readerbench/RoGPT2-base") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use readerbench/RoGPT2-base with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "readerbench/RoGPT2-base" # 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-base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/readerbench/RoGPT2-base
- SGLang
How to use readerbench/RoGPT2-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 "readerbench/RoGPT2-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": "readerbench/RoGPT2-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 "readerbench/RoGPT2-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": "readerbench/RoGPT2-base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use readerbench/RoGPT2-base with Docker Model Runner:
docker model run hf.co/readerbench/RoGPT2-base
Commit ·
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- config.json +1 -1
README.md
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Research supported with [Cloud TPUs](https://cloud.google.com/tpu/) from Google's [TensorFlow Research Cloud (TFRC)](https://www.tensorflow.org/tfrc)
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Research supported with [Cloud TPUs](https://cloud.google.com/tpu/) from Google's [TensorFlow Research Cloud (TFRC)](https://www.tensorflow.org/tfrc)
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## How to cite
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---
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Niculescu, M. A., Ruseti, S., and Dascalu, M. (submitted). RoGPT2: Romanian GPT2 for Text Generation
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config.json
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{
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"_name_or_path": "
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"activation_function": "gelu_new",
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"architectures": [
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"GPT2LMHeadModel"
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{
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"_name_or_path": "readerbench/RoGPT2-base",
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"activation_function": "gelu_new",
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"architectures": [
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"GPT2LMHeadModel"
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