Instructions to use eeeebbb2/2e1757fa-e7ea-4cbd-a525-25cfbc7a8444 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use eeeebbb2/2e1757fa-e7ea-4cbd-a525-25cfbc7a8444 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("jhflow/mistral7b-lora-multi-turn-v2") model = PeftModel.from_pretrained(base_model, "eeeebbb2/2e1757fa-e7ea-4cbd-a525-25cfbc7a8444") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4a57ad57d53574b19244db3be242b4ff15b1e8b304a376d31cc5c42d56af88bc
- Size of remote file:
- 6.84 kB
- SHA256:
- e3f099cde19c97777c4fb5c7652b4ff2c3f16b038d7e106310521c9612bf66d6
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