Instructions to use gszabo/large2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gszabo/large2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="gszabo/large2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("gszabo/large2") model = AutoModelForMaskedLM.from_pretrained("gszabo/large2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from gszabo/large2: direct link, hf CLI and curl.
- Browser
- Download file 6.28 MB
-
https://huggingface.co/gszabo/large2/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
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hf download hf://gszabo/large2@refs/pr/1/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/gszabo/large2/resolve/refs%2Fpr%2F1/tokenizer.json
6.28 MB
File too large to display, you can check the raw version instead.