Instructions to use tqfang229/deberta-v3-large-com2-atomic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tqfang229/deberta-v3-large-com2-atomic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="tqfang229/deberta-v3-large-com2-atomic")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("tqfang229/deberta-v3-large-com2-atomic") model = AutoModelForMaskedLM.from_pretrained("tqfang229/deberta-v3-large-com2-atomic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 30d9316275169fb34ceaad711dec1bbc61c5d94f88fba9f0378c843070c449ef
- Size of remote file:
- 1.92 kB
- SHA256:
- bb357eae91ca6dee772e1aa051d51d1ac15dfb3d6939fc85c99c233728675db4
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