Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use elopezlopez/Bio_ClinicalBERT_fold_10_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_10_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_10_binary_v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("elopezlopez/Bio_ClinicalBERT_fold_10_binary_v1") model = AutoModelForSequenceClassification.from_pretrained("elopezlopez/Bio_ClinicalBERT_fold_10_binary_v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from elopezlopez/Bio_ClinicalBERT_fold_10_binary_v1: direct link, hf CLI and curl.
- Browser
- Download file 3.38 kB
-
https://huggingface.co/elopezlopez/Bio_ClinicalBERT_fold_10_binary_v1/resolve/main/training_args.bin
- Command line
-
hf download hf://elopezlopez/Bio_ClinicalBERT_fold_10_binary_v1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/elopezlopez/Bio_ClinicalBERT_fold_10_binary_v1/resolve/main/training_args.bin
3.38 kB
- Xet hash:
- dfa764a408d8084a351986034e035ea505f9d463fa3c54b9479763808af61e31
- Size of remote file:
- 3.38 kB
- SHA256:
- 33e670e25d4c647d47677ee2a9c70e3eb24e67c857c33e02fe71a2d11145fb57
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