Instructions to use xtie/LLaMA-LoRA-PET-impression with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xtie/LLaMA-LoRA-PET-impression with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="xtie/LLaMA-LoRA-PET-impression")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("xtie/LLaMA-LoRA-PET-impression", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9819f88d8b5815718a333e260d0dbac1ab56c5a13b3ede69ff33d24272c5583b
- Size of remote file:
- 8.43 MB
- SHA256:
- 8fdebab0af5814c871d6d94013f2d74005206e86d4b042bbead8ede78ebfb356
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