Instructions to use hongngo/5b74ec1a-32ca-4c28-8dd0-901295780102 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use hongngo/5b74ec1a-32ca-4c28-8dd0-901295780102 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("teknium/OpenHermes-2.5-Mistral-7B") model = PeftModel.from_pretrained(base_model, "hongngo/5b74ec1a-32ca-4c28-8dd0-901295780102") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0db0dd30199e38cafaceb05b921af6db6d9859962e277f4187c2223d7da9c0ea
- Size of remote file:
- 83.9 MB
- SHA256:
- 57a13db07651da66eb8cb9477dae6a200a90c811051d2aa86f96e2d293323306
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