Instructions to use fredymad/bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fredymad/bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fredymad/bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fredymad/bert") model = AutoModelForSequenceClassification.from_pretrained("fredymad/bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4548c96f3356bf201b30e305720432940675c24f6fb3a1ef44df5081f82b9095
- Size of remote file:
- 438 MB
- SHA256:
- b6386c15f080b4a5abe4ea9bb075fe8683fb06ad4b3427d1b232f928befdfcdc
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