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
Librarian Bot: Update dataset YAML metadata for model
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README.md
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license: mit
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tags:
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- generated_from_trainer
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model-index:
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- name: BERiT
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results: []
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license: mit
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tags:
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- generated_from_trainer
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datasets: gngpostalsrvc/Tanakh
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model-index:
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- name: BERiT
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results: []
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