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:
- 278cffd9e58e675a4f171352cb0f2bbb331ba9dd779e52126a616a025ad1f1cb
- Size of remote file:
- 1.95 GB
- SHA256:
- f398311d79bb968d845b19dc938f9b27e2173267dbce72ef8b75be3eeba1c108
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