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 pytorch_model.bin from devkushal75/medtextclassifier: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/devkushal75/medtextclassifier/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://devkushal75/medtextclassifier/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/devkushal75/medtextclassifier/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 253d36a3301458966a85e3cf833654f887927365c69282da3a3527108b7daefc
- Size of remote file:
- 268 MB
- SHA256:
- 40b6f63a0d83198b3c20970d40c16c1950b9f59bba71d6150ed67c9309d35c1f
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