Instructions to use VCNC/bert_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VCNC/bert_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="VCNC/bert_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("VCNC/bert_2") model = AutoModelForSequenceClassification.from_pretrained("VCNC/bert_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from VCNC/bert_2: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/VCNC/bert_2/resolve/main/training_args.bin
- Command line
-
hf download hf://VCNC/bert_2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/VCNC/bert_2/resolve/main/training_args.bin
4.03 kB
- Xet hash:
- f5b070657f6b13d98aa6661bcfea7a57a0337e5bae654885286645ddd3c70c02
- Size of remote file:
- 4.03 kB
- SHA256:
- 13c8b3b2578eb0827ef7fc46072784378950a5687a74162940d7dc8e6c15718f
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