Instructions to use Surabhi-K/working with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Surabhi-K/working with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("codellama/CodeLlama-7b-hf") model = PeftModel.from_pretrained(base_model, "Surabhi-K/working") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 164972b0afac81813c57bc446e294599d608ac867c997852db04996cc3f0608c
- Size of remote file:
- 2.46 GB
- SHA256:
- 5e4ee88d37f55dc8c4972b83ba3bfc7ea1e52dcedefc5ce4d1b69ee96fbaf958
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