Instructions to use Madhour/gpt2-eli5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Madhour/gpt2-eli5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Madhour/gpt2-eli5")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Madhour/gpt2-eli5") model = AutoModelForCausalLM.from_pretrained("Madhour/gpt2-eli5") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Madhour/gpt2-eli5 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Madhour/gpt2-eli5" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Madhour/gpt2-eli5", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Madhour/gpt2-eli5
- SGLang
How to use Madhour/gpt2-eli5 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 "Madhour/gpt2-eli5" \ --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": "Madhour/gpt2-eli5", "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 "Madhour/gpt2-eli5" \ --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": "Madhour/gpt2-eli5", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Madhour/gpt2-eli5 with Docker Model Runner:
docker model run hf.co/Madhour/gpt2-eli5
| { | |
| "best_metric": 0.745124876499176, | |
| "best_model_checkpoint": "/content/checkpoint-250", | |
| "epoch": 2.0, | |
| "global_step": 250, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 1.0, | |
| "eval_loss": 0.7531784772872925, | |
| "eval_runtime": 102.2998, | |
| "eval_samples_per_second": 19.55, | |
| "eval_steps_per_second": 4.888, | |
| "step": 125 | |
| }, | |
| { | |
| "epoch": 2.0, | |
| "eval_loss": 0.745124876499176, | |
| "eval_runtime": 102.2807, | |
| "eval_samples_per_second": 19.554, | |
| "eval_steps_per_second": 4.889, | |
| "step": 250 | |
| } | |
| ], | |
| "max_steps": 500, | |
| "num_train_epochs": 4, | |
| "total_flos": 6271008768000000.0, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |