Instructions to use YCZhou/R2ANKER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YCZhou/R2ANKER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YCZhou/R2ANKER")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YCZhou/R2ANKER") model = AutoModelForSequenceClassification.from_pretrained("YCZhou/R2ANKER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from YCZhou/R2ANKER: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/YCZhou/R2ANKER/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://YCZhou/R2ANKER/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/YCZhou/R2ANKER/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- fc1718c5042cdde290c9c11bcc41f7626e35b4e5066c179ff713aa8a88e5ae88
- Size of remote file:
- 438 MB
- SHA256:
- 4c669dae7fe507ef0afbd81147ddbb03c7435652d1918f98c29796b215035345
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