Instructions to use jwna/ppo-gpt2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jwna/ppo-gpt2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="jwna/ppo-gpt2") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("jwna/ppo-gpt2") model = AutoModelForZeroShotImageClassification.from_pretrained("jwna/ppo-gpt2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download generation_config.json from jwna/ppo-gpt2: direct link, hf CLI and curl.
- Browser
- Download file 119 Bytes
-
https://huggingface.co/jwna/ppo-gpt2/resolve/main/generation_config.json
- Command line
-
hf download hf://jwna/ppo-gpt2/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/jwna/ppo-gpt2/resolve/main/generation_config.json
119 Bytes
| { | |
| "_from_model_config": true, | |
| "bos_token_id": 50256, | |
| "eos_token_id": 50256, | |
| "transformers_version": "4.47.1" | |
| } | |