Instructions to use mediabiasgroup/magpie-pt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mediabiasgroup/magpie-pt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mediabiasgroup/magpie-pt")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mediabiasgroup/magpie-pt") model = AutoModelForSequenceClassification.from_pretrained("mediabiasgroup/magpie-pt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from mediabiasgroup/magpie-pt: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/mediabiasgroup/magpie-pt/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://mediabiasgroup/magpie-pt/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/mediabiasgroup/magpie-pt/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- 950a4e134c1a8d15ac51fce677372348c97cb642fb525618b196f503fbb1bc36
- Size of remote file:
- 499 MB
- SHA256:
- 29c3575dab1cc0d09baf6ae675f0c51db9dca54bbee692228e0b5261f5854835
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