Instructions to use omarabb315/Arabic-Poem-Generator-Mega with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use omarabb315/Arabic-Poem-Generator-Mega with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="omarabb315/Arabic-Poem-Generator-Mega")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("omarabb315/Arabic-Poem-Generator-Mega") model = AutoModelForCausalLM.from_pretrained("omarabb315/Arabic-Poem-Generator-Mega") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use omarabb315/Arabic-Poem-Generator-Mega with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "omarabb315/Arabic-Poem-Generator-Mega" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "omarabb315/Arabic-Poem-Generator-Mega", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/omarabb315/Arabic-Poem-Generator-Mega
- SGLang
How to use omarabb315/Arabic-Poem-Generator-Mega 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 "omarabb315/Arabic-Poem-Generator-Mega" \ --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": "omarabb315/Arabic-Poem-Generator-Mega", "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 "omarabb315/Arabic-Poem-Generator-Mega" \ --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": "omarabb315/Arabic-Poem-Generator-Mega", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use omarabb315/Arabic-Poem-Generator-Mega with Docker Model Runner:
docker model run hf.co/omarabb315/Arabic-Poem-Generator-Mega
- Xet hash:
- 6a26fe1636d563660de528c0cb3d59ff9e121d18e70ed6758e91109133b7f2ce
- Size of remote file:
- 5.89 GB
- SHA256:
- f2de6ac275603c43b78cd3d4f49fb972b063d56b80532d0d0a8d6d693f8f8294
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.