Instructions to use Bebish/codebro-gpt2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bebish/codebro-gpt2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Bebish/codebro-gpt2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Bebish/codebro-gpt2") model = AutoModelForSequenceClassification.from_pretrained("Bebish/codebro-gpt2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aab2897300c2423ded3fbc571f91cba53836845f6283dd10f64a01ab37ceede7
- Size of remote file:
- 498 MB
- SHA256:
- 7818be98200427cdd45e8c8260102fa7b01fedf079da7cbe4e9635d84fcda94a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.