Instructions to use contemmcm/6431b2ccc01c99fe4ecf26fb75516f3e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use contemmcm/6431b2ccc01c99fe4ecf26fb75516f3e with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("contemmcm/6431b2ccc01c99fe4ecf26fb75516f3e") model = AutoModelForSeq2SeqLM.from_pretrained("contemmcm/6431b2ccc01c99fe4ecf26fb75516f3e", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d4b110643ed55086e4ce9f361afad7bb1d2ab1fdc5f92f498106ea4a0f5ea252
- Size of remote file:
- 5 GB
- SHA256:
- f452ae5f302d1429b944b09559b63d34778111c5e23afc5658e9594cc2b09069
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