Instructions to use earino/ecbs5200-week3-decoder-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use earino/ecbs5200-week3-decoder-lora with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="earino/ecbs5200-week3-decoder-lora")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("earino/ecbs5200-week3-decoder-lora") model = AutoModelForSequenceClassification.from_pretrained("earino/ecbs5200-week3-decoder-lora") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e59ff112818370d9addcb4af1db13df8e750e90eb25e0d40688ab01920e4b41e
- Size of remote file:
- 11.4 MB
- SHA256:
- 94e1c7e1e00a416c9b1b6b453b1cfb7bf5f6e7d3e018cb3f2b7eb09b09415b3c
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