Instructions to use FredZhang7/malphish-eater-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FredZhang7/malphish-eater-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="FredZhang7/malphish-eater-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("FredZhang7/malphish-eater-v1") model = AutoModelForSequenceClassification.from_pretrained("FredZhang7/malphish-eater-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1e82d902fc6d0c915050e65e6fc5994d10b74722bd2c099e8d7efcb298b27dba
- Size of remote file:
- 46.2 MB
- SHA256:
- 62c7deadf3ce71a98e77e1d67139a01950bbbf747e92b770e80b5b22d6669b25
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