Instructions to use shibajustfor/b0a2a05e-23f0-4fa7-97d5-312eb1c52a0e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use shibajustfor/b0a2a05e-23f0-4fa7-97d5-312eb1c52a0e with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/workspace/input_data/NousResearch/Meta-Llama-3-8B-Alternate-Tokenizer") model = PeftModel.from_pretrained(base_model, "shibajustfor/b0a2a05e-23f0-4fa7-97d5-312eb1c52a0e") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e8f731b848bf8e09ae8319239c5fadf3fb3065ed575c3e0736ef7917d50cb20f
- Size of remote file:
- 336 MB
- SHA256:
- d859bbb02d392e9e21471d8b26276c6dd1947c9971bf63a41c411782ee979d2b
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