Instructions to use lkwate/roberta-base-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lkwate/roberta-base-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="lkwate/roberta-base-mnli")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("lkwate/roberta-base-mnli") model = AutoModel.from_pretrained("lkwate/roberta-base-mnli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from lkwate/roberta-base-mnli: direct link, hf CLI and curl.
- Browser
- Download file 1.36 MB
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https://huggingface.co/lkwate/roberta-base-mnli/resolve/main/tokenizer.json
- Command line
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hf download hf://lkwate/roberta-base-mnli/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/lkwate/roberta-base-mnli/resolve/main/tokenizer.json
1.36 MB
File too large to display, you can check the raw version instead.