Text Generation
Transformers
PyTorch
TensorFlow
JAX
Safetensors
Italian
gpt2
adaption
recycled
gpt2-small
text-generation-inference
Instructions to use GroNLP/gpt2-small-italian with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GroNLP/gpt2-small-italian with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="GroNLP/gpt2-small-italian")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("GroNLP/gpt2-small-italian") model = AutoModelForCausalLM.from_pretrained("GroNLP/gpt2-small-italian", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use GroNLP/gpt2-small-italian with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "GroNLP/gpt2-small-italian" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "GroNLP/gpt2-small-italian", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/GroNLP/gpt2-small-italian
- SGLang
How to use GroNLP/gpt2-small-italian 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 "GroNLP/gpt2-small-italian" \ --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": "GroNLP/gpt2-small-italian", "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 "GroNLP/gpt2-small-italian" \ --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": "GroNLP/gpt2-small-italian", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use GroNLP/gpt2-small-italian with Docker Model Runner:
docker model run hf.co/GroNLP/gpt2-small-italian
Commit History
-
Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (d4bf9bc5e03fe59c8e9419c8576116034ed2ea1c) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>5ba4310
-
upload flax model
9a5b004 -
allow flax
5097fc8
-
fix link
092dc9a -
add bibtex
063fc89
-
fix language code
fa47e2a -
add model files
9ee6f2c -
initial commit
9c85459