Instructions to use leonweber/bunsen_base_last with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use leonweber/bunsen_base_last with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="leonweber/bunsen_base_last")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("leonweber/bunsen_base_last") model = AutoModel.from_pretrained("leonweber/bunsen_base_last") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b1fdb1958988dba71bca4842991f73cff5b6b854b07a99b065ae65477c1faf85
- Size of remote file:
- 433 MB
- SHA256:
- 4cc5f91130bb7388ae56d022ddcb701835594c91138d479ce493c803e124a103
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