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:
- 656d272a25703cddd98c4ec4de569f798bf8406514e1b5a265e69ff7b21e3fcf
- Size of remote file:
- 1.66 GB
- SHA256:
- dcf97efb2e4b60d813cb9578492e84940f18ff67dc0bd24a5f3cbf675b968f0a
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