Instructions to use WesScivetti/GPT-BERT_Random_Seed1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WesScivetti/GPT-BERT_Random_Seed1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="WesScivetti/GPT-BERT_Random_Seed1", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("WesScivetti/GPT-BERT_Random_Seed1", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b84717933aba04a036e6cfffeebb7557c3e7d19d3cf64dbcb1605878548e387d
- Size of remote file:
- 503 MB
- SHA256:
- 5b96fec17eb64135f3c51853ca79a1e8a19f639bfb021ff71ac13c3b476a134c
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