Instructions to use mgh6/temp2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mgh6/temp2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mgh6/temp2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("mgh6/temp2") model = AutoModelForMaskedLM.from_pretrained("mgh6/temp2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8c854da1e60eca3a4e015fca3529fdb5eee7190676c222c8161c65bac08279cd
- Size of remote file:
- 136 MB
- SHA256:
- 31b6957e0d60ae77efde839f94a53a304d327bd8318c903259788ac772b03c6e
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