Instructions to use atom92/medical2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use atom92/medical2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="atom92/medical2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("atom92/medical2") model = AutoModelForSequenceClassification.from_pretrained("atom92/medical2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from atom92/medical2: direct link, hf CLI and curl.
- Browser
- Download file 536 MB
-
https://huggingface.co/atom92/medical2/resolve/main/optimizer.pt
- Command line
-
hf download hf://atom92/medical2/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/atom92/medical2/resolve/main/optimizer.pt
536 MB
- Xet hash:
- 363fc7e16abaad65b6ee6442d69bf9ade686f6bb5dc246b09cf59c5181744e1c
- Size of remote file:
- 536 MB
- SHA256:
- d4b322c6ba24ee5f947856ad2010a55fe4893e4f46f44a507d81aaa0b7a8b223
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