Instructions to use baltop/cdp_300 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use baltop/cdp_300 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_300") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 75cbf894defcc8d17497b6dec97c040c8465f5821a71e84688bfd1c750624612
- Size of remote file:
- 85.7 MB
- SHA256:
- 490da2a75851a94524c7a46cd703bff5275954c3fc2b9b104b81ccc6549e5d48
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