Text Generation
Transformers
PyTorch
TensorFlow
JAX
TensorBoard
Persian
gpt2
text-generation-inference
Instructions to use flax-community/gpt2-medium-persian with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flax-community/gpt2-medium-persian with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="flax-community/gpt2-medium-persian")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("flax-community/gpt2-medium-persian") model = AutoModelForCausalLM.from_pretrained("flax-community/gpt2-medium-persian") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use flax-community/gpt2-medium-persian with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "flax-community/gpt2-medium-persian" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "flax-community/gpt2-medium-persian", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/flax-community/gpt2-medium-persian
- SGLang
How to use flax-community/gpt2-medium-persian 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 "flax-community/gpt2-medium-persian" \ --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": "flax-community/gpt2-medium-persian", "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 "flax-community/gpt2-medium-persian" \ --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": "flax-community/gpt2-medium-persian", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use flax-community/gpt2-medium-persian with Docker Model Runner:
docker model run hf.co/flax-community/gpt2-medium-persian
- Xet hash:
- 6d16813d316e685f96925f4302b0bd2817734b556711409df870be051ff3fb8f
- Size of remote file:
- 1.42 GB
- SHA256:
- 022e3c438752023ce7d26b0bb58fbc27b1cf86b534aa8fbb6119713dba36fa6e
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