Instructions to use WesScivetti/GPT-BERT_Random_Seed3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WesScivetti/GPT-BERT_Random_Seed3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="WesScivetti/GPT-BERT_Random_Seed3", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("WesScivetti/GPT-BERT_Random_Seed3", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d0ebd1bf22f8a9aeb11b0ff135c9e41a8a39c72093152ce47d66c45e8630d3d4
- Size of remote file:
- 503 MB
- SHA256:
- a2ca67eafde5cbb9d32d2efc326d9d251cb71bbc99273edf8047de222486aa78
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