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:
- 7ca93d7ee84cc3b9ee830a2bfd6dd83190c03c1d310efa9246df1a667dc16948
- Size of remote file:
- 4.98 GB
- SHA256:
- 8ffcd745f6d1de75bbcd76605453dd3afa86c8bf84ff113aa772922e354fc2bc
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