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:
- b2d998e775121058049fb93d4d267183cba57a4e484b139c75c1c91f987e230a
- Size of remote file:
- 4.96 MB
- SHA256:
- 6930bf12ee29fb14611b2c7c3a1332f1b8f162c24e5579150bbe626ab674704f
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