Instructions to use baltop/cdp_600 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use baltop/cdp_600 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.1") model = PeftModel.from_pretrained(base_model, "baltop/cdp_600") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f77242314aef0a29d0fdf79b8c26ac32e91457d82810d8c5c5f40f102e83e985
- Size of remote file:
- 85.7 MB
- SHA256:
- 44380c0217d17ef174c0adaaf6d5df036f861e8b8a285a9e81331e48f5d04c1e
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