Instructions to use gngpostalsrvc/BERiT_2000_ls_.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gngpostalsrvc/BERiT_2000_ls_.2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="gngpostalsrvc/BERiT_2000_ls_.2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("gngpostalsrvc/BERiT_2000_ls_.2") model = AutoModelForMaskedLM.from_pretrained("gngpostalsrvc/BERiT_2000_ls_.2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 48f43773b871a9ce7f96efcba495f437cff00b695ab47c6f278c31561899dd34
- Size of remote file:
- 3.44 kB
- SHA256:
- 9400f34df4d6566416d92c82494333943bde36637522ad629feba4e5a733817c
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