Instructions to use MaCoCu/MaltBERTa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MaCoCu/MaltBERTa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="MaCoCu/MaltBERTa")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("MaCoCu/MaltBERTa") model = AutoModel.from_pretrained("MaCoCu/MaltBERTa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a4193daa48604cad38ba3991766469dd65e09fb89649e52366c73149fd74e733
- Size of remote file:
- 442 MB
- SHA256:
- 3b10d48d2d3be0159a83e7f02b9491fa75db486fb36fbed3c7e30678731a52ca
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