Instructions to use imamnurby/RoBERTduino_uncased_w_methods with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use imamnurby/RoBERTduino_uncased_w_methods with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="imamnurby/RoBERTduino_uncased_w_methods")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("imamnurby/RoBERTduino_uncased_w_methods") model = AutoModel.from_pretrained("imamnurby/RoBERTduino_uncased_w_methods", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 88df93df95264575e600d881c8a1b7750c00dea4802fae10aa1ab1578e51af71
- Size of remote file:
- 499 MB
- SHA256:
- efb3db281eee4153728dab7b1e0c62ef3ea7d00d688807c5e73089c8f56fc5fb
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