Instructions to use dtorber/bertweet-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dtorber/bertweet-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dtorber/bertweet-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dtorber/bertweet-base") model = AutoModelForSequenceClassification.from_pretrained("dtorber/bertweet-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from dtorber/bertweet-base: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/dtorber/bertweet-base/resolve/main/training_args.bin
- Command line
-
hf download hf://dtorber/bertweet-base/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dtorber/bertweet-base/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- d75807ee2ed597b5a437200ead3f91bda8c9864c7c730385e399b4b839ad9300
- Size of remote file:
- 5.18 kB
- SHA256:
- d7877fc824c72150fc3c12e5344ab10f2387044c4cf9579c251598ec1872bc3d
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