Instructions to use contemmcm/702802ca759e8c681985de9fada58d4e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use contemmcm/702802ca759e8c681985de9fada58d4e with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("contemmcm/702802ca759e8c681985de9fada58d4e") model = AutoModelForSeq2SeqLM.from_pretrained("contemmcm/702802ca759e8c681985de9fada58d4e", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 49e18c6e461254ed002e698e5d8be3557e3e3f69733f6eb9b410370981d7b82a
- Size of remote file:
- 16.8 MB
- SHA256:
- 20a46ac256746594ed7e1e3ef733b83fbc5a6f0922aa7480eda961743de080ef
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.