Instructions to use contemmcm/df9829ef20751e04c89354d87ebedc3c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use contemmcm/df9829ef20751e04c89354d87ebedc3c with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("contemmcm/df9829ef20751e04c89354d87ebedc3c") model = AutoModelForSeq2SeqLM.from_pretrained("contemmcm/df9829ef20751e04c89354d87ebedc3c", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 37a3266e86fbf3ebc77ab35f3adcba673588f3019214df99341075959d612e3b
- Size of remote file:
- 5 GB
- SHA256:
- 1eb7a5615623192da9d785a569cf275e36a60f582a674acbe2d33d16a71aad82
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