Instructions to use JimK28/gpt-bert-entmax-graded with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JimK28/gpt-bert-entmax-graded with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="JimK28/gpt-bert-entmax-graded", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("JimK28/gpt-bert-entmax-graded", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e651d5f74494397ce0fa8de5e07a650e8d70a70d37e1e681eefd91dd6910d76c
- Size of remote file:
- 120 MB
- SHA256:
- 08b29b80f734260e1dec149577149acfb49ee4003bfb3eb4e72a4b04f74e7273
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