Instructions to use contemmcm/5a621a2ee9af95198a887713042d601b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use contemmcm/5a621a2ee9af95198a887713042d601b with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("contemmcm/5a621a2ee9af95198a887713042d601b") model = AutoModelForSeq2SeqLM.from_pretrained("contemmcm/5a621a2ee9af95198a887713042d601b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e3a3e20392025c4c56b4b990f701d675ede8446052aa785960aa5b9a77176745
- Size of remote file:
- 1.02 GB
- SHA256:
- 422963cbf790ce81028b790b03e6d48bc20da104328b3b07b74e8462f42d1214
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