Instructions to use mnaylor/base-bert-finetuned-mtsamples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mnaylor/base-bert-finetuned-mtsamples with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mnaylor/base-bert-finetuned-mtsamples")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mnaylor/base-bert-finetuned-mtsamples") model = AutoModelForSequenceClassification.from_pretrained("mnaylor/base-bert-finetuned-mtsamples", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Mitch Naylor commited on
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# BERT Base Fine-tuned on MTSamples
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This model is [BERT-base](https://huggingface.co/bert-base-uncased) fine-tuned on the MTSamples dataset, with a classification task defined in [this repo](https://github.com/socd06/medical-nlp).
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