Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use elopezlopez/Bio_ClinicalBERT_fold_9_binary_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use elopezlopez/Bio_ClinicalBERT_fold_9_binary_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="elopezlopez/Bio_ClinicalBERT_fold_9_binary_v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("elopezlopez/Bio_ClinicalBERT_fold_9_binary_v1") model = AutoModelForSequenceClassification.from_pretrained("elopezlopez/Bio_ClinicalBERT_fold_9_binary_v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from elopezlopez/Bio_ClinicalBERT_fold_9_binary_v1: direct link, hf CLI and curl.
- Browser
- Download file 3.38 kB
-
https://huggingface.co/elopezlopez/Bio_ClinicalBERT_fold_9_binary_v1/resolve/main/training_args.bin
- Command line
-
hf download hf://elopezlopez/Bio_ClinicalBERT_fold_9_binary_v1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/elopezlopez/Bio_ClinicalBERT_fold_9_binary_v1/resolve/main/training_args.bin
3.38 kB
- Xet hash:
- 1b9a77158d72a2f4f90d37b2d26593fa3a7613b6d05aa616e8d39986d594266a
- Size of remote file:
- 3.38 kB
- SHA256:
- ea0290944eb4eff854420f9255e75e86b64cc73f2f5ff0a7bd23d21cceac30a3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.