Instructions to use OATML-Markslab/Tranception_Medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OATML-Markslab/Tranception_Medium with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="OATML-Markslab/Tranception_Medium")# Load model directly from transformers import AutoModelWithLMHead model = AutoModelWithLMHead.from_pretrained("OATML-Markslab/Tranception_Medium", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 440b70e36ac9e8c2c7093408db94c8cc04e4d30ccad8b2b34c2e3736d0edfe5c
- Size of remote file:
- 1.24 GB
- SHA256:
- d7733a0eed60a9a2f4543abc09d468591eb5c1ccdec975e8b012a4c2f78d09e0
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