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
- 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
Commit History
Fix some bugs d19a8a5
Add log info 3733ce3
Update runner 51b14d7
Add dataset creation script c92ce97
change run.sh 70704f2
pushing tokenizer c36ebf7
Add runner, fix some bugs 31bf2aa
Merge remote-tracking branch 'origin/saied' into develop 8918872
Remove junks a749413
adding remove add and remove tag functions a32918a
Remove extra file 4350a5a
Add normalization steps, fix som bugs, add tfboard tracker 1809a17
Refine saied code 09f9c26
some modification in preprocessing/urls removing ad582b6
some modification in preprocessing 79fa2a7
editted data_utils-url,html,streched alphabet 95cd35a
Fix rm files bce7e0a
Add training script with checkpoint and preprocessing + merge scripts 7cfca48
Merge remote-tracking branch 'origin/hooman' into develop 8812e32
adding dataset prepration module 73d5951
pushing a template clm training script for gpt2 01ae861
Hooman Sedghamiz commited on