Instructions to use cariai/meds with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cariai/meds with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="cariai/meds")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("cariai/meds") model = AutoModelForTokenClassification.from_pretrained("cariai/meds", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from cariai/meds: direct link, hf CLI and curl.
- Browser
- Download file 496 MB
-
https://huggingface.co/cariai/meds/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://cariai/meds/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/cariai/meds/resolve/main/flax_model.msgpack
496 MB
- Xet hash:
- e71249215910d37a13b063f3891ed88d1720edc50d32e535ce89bf89b5dcc28f
- Size of remote file:
- 496 MB
- SHA256:
- e0e1569a683eb4e6da9250f62f76acec79cf30c13b859ce0ba05bfedb7e20c4c
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