Instructions to use johngreendr1/72bfe024-efd2-4674-93c0-88d64ac0da4c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use johngreendr1/72bfe024-efd2-4674-93c0-88d64ac0da4c with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5") model = PeftModel.from_pretrained(base_model, "johngreendr1/72bfe024-efd2-4674-93c0-88d64ac0da4c") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 070ba31edb0629ee183e9d3d1e83f48f72bbb584ff56c6c30bb658102e24661e
- Size of remote file:
- 1.51 GB
- SHA256:
- 4b41023bc05bddc7023584eece7d745ed85372cf83511baa3b7c1de88d6f843a
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