Instructions to use aiface/velectra-base_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aiface/velectra-base_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aiface/velectra-base_v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aiface/velectra-base_v2") model = AutoModelForSequenceClassification.from_pretrained("aiface/velectra-base_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from aiface/velectra-base_v2: direct link, hf CLI and curl.
- Browser
- Download file 5.91 kB
-
https://huggingface.co/aiface/velectra-base_v2/resolve/main/training_args.bin
- Command line
-
hf download hf://aiface/velectra-base_v2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/aiface/velectra-base_v2/resolve/main/training_args.bin
5.91 kB
- Xet hash:
- bbdf6fe35d149ad621e6e35405706b328683bc5e3f6d11e80b125906cddb8cb7
- Size of remote file:
- 5.91 kB
- SHA256:
- 9a9868f4697b20a5e0771253a54a6669a6426b3a6a4a253afc7643a2118b4864
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