Instructions to use myxik/medhack with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use myxik/medhack with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="myxik/medhack")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("myxik/medhack") model = AutoModelForTokenClassification.from_pretrained("myxik/medhack", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1a2914b4204c3b764860f92a2652813f883ff763605488564d66c5c3d4d2bee9
- Size of remote file:
- 539 MB
- SHA256:
- 79014ff34cc3baf4d9e371a897338b4e05aeb192a2852fa0591d3b6464cede2e
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