Instructions to use mmoradi/Robust-Biomed-RoBERTa-TextClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mmoradi/Robust-Biomed-RoBERTa-TextClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="mmoradi/Robust-Biomed-RoBERTa-TextClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("mmoradi/Robust-Biomed-RoBERTa-TextClassification") model = AutoModel.from_pretrained("mmoradi/Robust-Biomed-RoBERTa-TextClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Upload vocab.json
feb1f69 -
Upload tokenizer_config.json
ec52b90 -
Upload special_tokens_map.json
6886aeb -
Upload pytorch_model.bin with git-lfs
92f19e7 -
Upload processor_config.json
24a1779 -
Upload prediction_head_0_config.json
862d952 -
Upload prediction_head_0.bin with git-lfs
90adbb9 -
Upload merges.txt
02b9f64 -
Upload flax_model.msgpack with git-lfs
ad6cc64 -
Upload config.json
9a4e6c2 -
initial commit
8e4e151