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:
- f7f3e49ce5c7f778225dceda28f1ab0c31f50eaafd1fbaa0250235426f0f4cd2
- Size of remote file:
- 3.58 kB
- SHA256:
- 32d5a1386ad256ea322c8264d193767436c14228a3532c68bbc883c696ad900e
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