Instructions to use Tristan/gpt2_summarization_reward_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tristan/gpt2_summarization_reward_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Tristan/gpt2_summarization_reward_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Tristan/gpt2_summarization_reward_model") model = AutoModelForSequenceClassification.from_pretrained("Tristan/gpt2_summarization_reward_model") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
#2 opened over 2 years ago
by
librarian-bot
Adding `safetensors` variant of this model
#1 opened about 3 years ago
by
SFconvertbot