Instructions to use gngpostalsrvc/BERiT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gngpostalsrvc/BERiT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="gngpostalsrvc/BERiT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("gngpostalsrvc/BERiT") model = AutoModelForMaskedLM.from_pretrained("gngpostalsrvc/BERiT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 617d2d94b4500c87738d28292c585953b9e41c78fd6ff704c912e4a0dd09511c
- Size of remote file:
- 5.68 MB
- SHA256:
- e848bb0b1818d99d7e162bfa29a2960b425cbaff6eea3da946a112f7fc57532f
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