Instructions to use mamamiya405/alpaca_lora_doc_summary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mamamiya405/alpaca_lora_doc_summary with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("decapoda-research/llama-7b-hf") model = PeftModel.from_pretrained(base_model, "mamamiya405/alpaca_lora_doc_summary") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8f2a24cc799da1523c13aac1a64397e1f83f747369059aeb77b3c9935a0baa05
- Size of remote file:
- 16.8 MB
- SHA256:
- 126191b59f9ba98ade545b93e9e7441e9735eccd14d58a9a57c4842901b2e880
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