Instructions to use HooshvareLab/roberta-fa-zwnj-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HooshvareLab/roberta-fa-zwnj-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="HooshvareLab/roberta-fa-zwnj-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("HooshvareLab/roberta-fa-zwnj-base") model = AutoModelForMaskedLM.from_pretrained("HooshvareLab/roberta-fa-zwnj-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- be319c790de20b314d2bbb55f8e790a28bf979c6c2644fe98d5a065dadfe3e45
- Size of remote file:
- 473 MB
- SHA256:
- 2293b33bbb807e74906994ef6a6c7537856f82cdec73f097c6f461f333db7f0f
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