Instructions to use zhuqing/roberta-base-uncased-netmums-classification-intersection-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zhuqing/roberta-base-uncased-netmums-classification-intersection-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="zhuqing/roberta-base-uncased-netmums-classification-intersection-2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("zhuqing/roberta-base-uncased-netmums-classification-intersection-2") model = AutoModelForSequenceClassification.from_pretrained("zhuqing/roberta-base-uncased-netmums-classification-intersection-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from zhuqing/roberta-base-uncased-netmums-classification-intersection-2: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/zhuqing/roberta-base-uncased-netmums-classification-intersection-2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://zhuqing/roberta-base-uncased-netmums-classification-intersection-2/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/zhuqing/roberta-base-uncased-netmums-classification-intersection-2/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- 369451a34338238d877d61e0eea1502a105461ca3af1f3695748fb37f5a19026
- Size of remote file:
- 499 MB
- SHA256:
- af4e2afa435d0a2b5f6f11d3f474ad8ff1569bd7bf7906456950b58a64fc537c
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