Instructions to use gszabo/base_webcorpus2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gszabo/base_webcorpus2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="gszabo/base_webcorpus2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("gszabo/base_webcorpus2") model = AutoModelForMaskedLM.from_pretrained("gszabo/base_webcorpus2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 78 Bytes
ad40234 | 1 2 3 4 5 | {
"model_max_length": 512,
"tokenizer_class": "PreTrainedTokenizerFast"
}
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