Instructions to use apugachev/roberta-large-boolq-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use apugachev/roberta-large-boolq-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="apugachev/roberta-large-boolq-finetuned")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("apugachev/roberta-large-boolq-finetuned") model = AutoModelForSequenceClassification.from_pretrained("apugachev/roberta-large-boolq-finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from apugachev/roberta-large-boolq-finetuned: direct link, hf CLI and curl.
- Browser
- Download file 3.18 kB
-
https://huggingface.co/apugachev/roberta-large-boolq-finetuned/resolve/main/training_args.bin
- Command line
-
hf download hf://apugachev/roberta-large-boolq-finetuned/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/apugachev/roberta-large-boolq-finetuned/resolve/main/training_args.bin
3.18 kB
- Xet hash:
- e218e9cd695572f8ff54d4bd8b1be7681ca389582a8ee9b063e96f555ac5a095
- Size of remote file:
- 3.18 kB
- SHA256:
- 412e90cc780e84b53e2823c8fe3558398ca937786addff512d86f92a556d0b27
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