Instructions to use daze-unlv/LennartKeller-nystromformer-gottbert-base-8192 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use daze-unlv/LennartKeller-nystromformer-gottbert-base-8192 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMultipleChoice tokenizer = AutoTokenizer.from_pretrained("daze-unlv/LennartKeller-nystromformer-gottbert-base-8192") model = AutoModelForMultipleChoice.from_pretrained("daze-unlv/LennartKeller-nystromformer-gottbert-base-8192", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from daze-unlv/LennartKeller-nystromformer-gottbert-base-8192: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/daze-unlv/LennartKeller-nystromformer-gottbert-base-8192/resolve/main/training_args.bin
- Command line
-
hf download hf://daze-unlv/LennartKeller-nystromformer-gottbert-base-8192/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/daze-unlv/LennartKeller-nystromformer-gottbert-base-8192/resolve/main/training_args.bin
4.98 kB
- Xet hash:
- eea65f8a42e976b1a77479910f116c40bd7087c1fe15ee1ffb75df7fa1bb2282
- Size of remote file:
- 4.98 kB
- SHA256:
- 5e2ef03073c59c4ff1e392b7d1b806e2b027cd288214569d15af9bf3c34ac696
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