Instructions to use TigerByteCyber/roberta-large-zeroshot-v2.0-c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TigerByteCyber/roberta-large-zeroshot-v2.0-c with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="TigerByteCyber/roberta-large-zeroshot-v2.0-c")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TigerByteCyber/roberta-large-zeroshot-v2.0-c") model = AutoModelForSequenceClassification.from_pretrained("TigerByteCyber/roberta-large-zeroshot-v2.0-c", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2fed88a4c80ee9368c042ae9f90177be9863ad7f96d79d74fc6a638e98cd84b5
- Size of remote file:
- 4.86 kB
- SHA256:
- eaeda9c4882246851fe97d7679b0640d01b8b36d31cd86f0b042e44371c440ba
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