Instructions to use BayesTensor/modernbert_seeker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BayesTensor/modernbert_seeker with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BayesTensor/modernbert_seeker")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BayesTensor/modernbert_seeker") model = AutoModelForSequenceClassification.from_pretrained("BayesTensor/modernbert_seeker", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from BayesTensor/modernbert_seeker: direct link, hf CLI and curl.
- Browser
- Download file 5.43 kB
-
https://huggingface.co/BayesTensor/modernbert_seeker/resolve/main/training_args.bin
- Command line
-
hf download hf://BayesTensor/modernbert_seeker/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/BayesTensor/modernbert_seeker/resolve/main/training_args.bin
5.43 kB
- Xet hash:
- 4d1c49183bd97c58d0f7a0049c5b5d976396543ad8ed8f95f4b059aefef9d540
- Size of remote file:
- 5.43 kB
- SHA256:
- b7328b3b82d74097e3578d8ec360a3b4618539c7ff39b0d2fab35fa19a4d431d
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