Instructions to use IVN-RIN/medBIT-r3-plus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IVN-RIN/medBIT-r3-plus with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="IVN-RIN/medBIT-r3-plus")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("IVN-RIN/medBIT-r3-plus") model = AutoModelForMaskedLM.from_pretrained("IVN-RIN/medBIT-r3-plus", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from IVN-RIN/medBIT-r3-plus: direct link, hf CLI and curl.
- Browser
- Download file 724 kB
-
https://huggingface.co/IVN-RIN/medBIT-r3-plus/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
-
hf download hf://IVN-RIN/medBIT-r3-plus@refs/pr/1/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/IVN-RIN/medBIT-r3-plus/resolve/refs%2Fpr%2F1/tokenizer.json
724 kB
File too large to display, you can check the raw version instead.