Instructions to use Ghunghru/Misinformation-Covid-LowLearningRatebert-base-multilingual-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ghunghru/Misinformation-Covid-LowLearningRatebert-base-multilingual-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ghunghru/Misinformation-Covid-LowLearningRatebert-base-multilingual-cased")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ghunghru/Misinformation-Covid-LowLearningRatebert-base-multilingual-cased") model = AutoModelForSequenceClassification.from_pretrained("Ghunghru/Misinformation-Covid-LowLearningRatebert-base-multilingual-cased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Ghunghru/Misinformation-Covid-LowLearningRatebert-base-multilingual-cased: direct link, hf CLI and curl.
- Browser
- Download file 4.6 kB
-
https://huggingface.co/Ghunghru/Misinformation-Covid-LowLearningRatebert-base-multilingual-cased/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://Ghunghru/Misinformation-Covid-LowLearningRatebert-base-multilingual-cased@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Ghunghru/Misinformation-Covid-LowLearningRatebert-base-multilingual-cased/resolve/refs%2Fpr%2F1/training_args.bin
4.6 kB
- Xet hash:
- 26964e0f0ade754b7ab2e2da46f4132fe229146be2130c688fec8795c9810111
- Size of remote file:
- 4.6 kB
- SHA256:
- cb03b8529ec2692af3b1ff9cd195120f5e83c0097aa2d3b6df137265d85bbdbc
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