Instructions to use devkushal75/medtextclassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devkushal75/medtextclassifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="devkushal75/medtextclassifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("devkushal75/medtextclassifier") model = AutoModelForSequenceClassification.from_pretrained("devkushal75/medtextclassifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from devkushal75/medtextclassifier: direct link, hf CLI and curl.
- Browser
- Download file 536 MB
-
https://huggingface.co/devkushal75/medtextclassifier/resolve/main/optimizer.pt
- Command line
-
hf download hf://devkushal75/medtextclassifier/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/devkushal75/medtextclassifier/resolve/main/optimizer.pt
536 MB
- Xet hash:
- 0957ca9dfa344253dbd4c9071129534c7f5f76603518565c1b53a3343eb1f0bb
- Size of remote file:
- 536 MB
- SHA256:
- 5aeab51ff2c0c45e10f583767ad58da9f90e6d12215e923ff49f54b84dde8a53
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