Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use sid321axn/Bio_ClinicalBERT-finetuned-medicalcondition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sid321axn/Bio_ClinicalBERT-finetuned-medicalcondition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sid321axn/Bio_ClinicalBERT-finetuned-medicalcondition")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sid321axn/Bio_ClinicalBERT-finetuned-medicalcondition") model = AutoModelForSequenceClassification.from_pretrained("sid321axn/Bio_ClinicalBERT-finetuned-medicalcondition", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from sid321axn/Bio_ClinicalBERT-finetuned-medicalcondition: direct link, hf CLI and curl.
- Browser
- Download file 433 MB
-
https://huggingface.co/sid321axn/Bio_ClinicalBERT-finetuned-medicalcondition/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://sid321axn/Bio_ClinicalBERT-finetuned-medicalcondition/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sid321axn/Bio_ClinicalBERT-finetuned-medicalcondition/resolve/main/pytorch_model.bin
433 MB
- Xet hash:
- b1c2ab4899e7cf9448d0500fd3279ebe7789d3f5e1635f000c366820a51a9f75
- Size of remote file:
- 433 MB
- SHA256:
- 479fc13fd4c709ea943882bbd5c2d6216626c2ae31714a60f438f58b98d71b45
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.