Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use elopezlopez/Bio_ClinicalBERT_fold_8_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_8_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_8_binary_v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("elopezlopez/Bio_ClinicalBERT_fold_8_binary_v1") model = AutoModelForSequenceClassification.from_pretrained("elopezlopez/Bio_ClinicalBERT_fold_8_binary_v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from elopezlopez/Bio_ClinicalBERT_fold_8_binary_v1: direct link, hf CLI and curl.
- Browser
- Download file 3.38 kB
-
https://huggingface.co/elopezlopez/Bio_ClinicalBERT_fold_8_binary_v1/resolve/main/training_args.bin
- Command line
-
hf download hf://elopezlopez/Bio_ClinicalBERT_fold_8_binary_v1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/elopezlopez/Bio_ClinicalBERT_fold_8_binary_v1/resolve/main/training_args.bin
3.38 kB
- Xet hash:
- bcd31d6b1961e8440df02741d9f60e8703dea51406cbe5df256788addb0e65c3
- Size of remote file:
- 3.38 kB
- SHA256:
- 68d819e35bf12b2118dd9afd50b6ee92636dfcfee3023b1f7d90d37f20c980c5
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