Instructions to use ipipan/herference-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ipipan/herference-large with Transformers:
# Load model directly from transformers import AutoTokenizer, S2E tokenizer = AutoTokenizer.from_pretrained("ipipan/herference-large") model = S2E.from_pretrained("ipipan/herference-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b2467f0c0225020663182d8ceee8ca0b3f7365d10fc7d029fc25064c8bddd7d5
- Size of remote file:
- 1.69 MB
- SHA256:
- fbc62dec863a5a04aed5bf43d7454d41606db186e9014ed0f6598dd29e006480
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