Instructions to use edbeeching/gpt2_stack-exchange-paired_reward_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use edbeeching/gpt2_stack-exchange-paired_reward_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="edbeeching/gpt2_stack-exchange-paired_reward_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("edbeeching/gpt2_stack-exchange-paired_reward_model") model = AutoModelForSequenceClassification.from_pretrained("edbeeching/gpt2_stack-exchange-paired_reward_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Upload tokenizer
c1de2bc -
Upload GPT2ForSequenceClassification
04f05ac -
Upload tokenizer
0dd52ac -
Upload GPT2ForSequenceClassification
8d5cc0a -
Upload tokenizer
b22acef -
Upload GPT2ForSequenceClassification
19865ce -
initial commit
fff92d6