Instructions to use microsoft/longcoder-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/longcoder-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="microsoft/longcoder-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("microsoft/longcoder-base") model = AutoModelForMultimodalLM.from_pretrained("microsoft/longcoder-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 668e58fa683ced299449dfde8a3bf52b91add81c0e1edd27d5c8caa8e0f1cbb7
- Size of remote file:
- 598 MB
- SHA256:
- fde67a1823e80f44c0749b245d7365835be2f1e78221665eabc714bff25116e0
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