Instructions to use textattack/roberta-base-MNLI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/roberta-base-MNLI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/roberta-base-MNLI")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/roberta-base-MNLI") model = AutoModelForSequenceClassification.from_pretrained("textattack/roberta-base-MNLI", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from textattack/roberta-base-MNLI: direct link, hf CLI and curl.
- Browser
- Download file 1.03 kB
-
https://huggingface.co/textattack/roberta-base-MNLI/resolve/main/training_args.bin
- Command line
-
hf download hf://textattack/roberta-base-MNLI/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/textattack/roberta-base-MNLI/resolve/main/training_args.bin
1.03 kB
- Xet hash:
- 22fb93ad0b365d655fab13acb4da14704be59d945b0a5cbb61a2292530fca418
- Size of remote file:
- 1.03 kB
- SHA256:
- 1151f8b17c30b213b7d70d37e78c3af619c5a83cfb0ee9af4b18c4fad00290c1
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