Instructions to use BayesTensor/debertas_seeker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BayesTensor/debertas_seeker with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BayesTensor/debertas_seeker")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BayesTensor/debertas_seeker") model = AutoModelForSequenceClassification.from_pretrained("BayesTensor/debertas_seeker", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from BayesTensor/debertas_seeker: direct link, hf CLI and curl.
- Browser
- Download file 5.43 kB
-
https://huggingface.co/BayesTensor/debertas_seeker/resolve/main/training_args.bin
- Command line
-
hf download hf://BayesTensor/debertas_seeker/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/BayesTensor/debertas_seeker/resolve/main/training_args.bin
5.43 kB
- Xet hash:
- 9d7c1bb99ac69aaf62a54e81c031ddbf48a4deb132277ea5404bccadf6b84798
- Size of remote file:
- 5.43 kB
- SHA256:
- 1a4cef7ab6f4ff209dd756db3bbb721abd11ddfea5e6d59d89d58906d87bc93f
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